research topics on software engineering

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What are Software Engineer Research Topics?

Software engineer research topics are areas of exploration and study in the rapidly evolving field of software engineering. These research topics include various software development approaches, quality of software, testing of software, maintenance of software, security measures for software, machine learning models in software engineering, DevOps, and architecture of software. Each of these software engineer research topics has distinct problems and opportunities for software engineers to investigate and make major contributions to the field. In short, research topics for software engineering provide possibilities for software engineers to investigate new technologies, approaches, and strategies for developing and managing complex software systems.

For example, research on agile software development could identify the benefits and drawbacks of using agile methodology, as well as develop new techniques for effectively implementing agile practices. Software testing research may explore new testing procedures and tools, as well as assess the efficacy of existing ones. Software quality research may investigate the elements that influence software quality and develop approaches for enhancing software system quality and minimizing the faults and errors. Software metrics are quantitative measures that are used to assess the quality, maintainability, and performance of software.

The research papers on software engineering topics in this specific area could identify novel measures for evaluating software systems or techniques for using metrics to improve the quality of software. The practice of integrating code changes into a common repository and pushing code changes to production in small, periodic batches is known as continuous integration and deployment (CI/CD). This research could investigate the best practices for establishing CI/CD or developing tools and approaches for automating the entire CI/CD process.

2. Natural Language Processing

Multimodality

Multimodality in Natural Language Processing (NLP) is one of the appealing research ideas for software engineering at the nexus of computer vision, speech recognition, and NLP. The ability of machines to comprehend and generate language from many modalities, such as text, speech, pictures, and video, is referred to as multimodal NLP. The goal of multimodal NLP is to develop systems that can learn from and interpret human communication across several modalities, allowing them to engage with humans in more organic and intuitive ways.

The building of conversational agents or chatbots that can understand and create responses using several modalities is one example of multimodal NLP in action. These agents can analyze text input, voice input, and visual clues to provide more precise and relevant responses, allowing users to have a more natural and seamless conversational experience. Furthermore, multimodal NLP can be used to enhance language translation systems, allowing them to more accurately and effectively translate text, speech, and visual content.

The development of multimodal NLP systems must take efficiency into account. as multimodal NLP systems require significant computing power to process and integrate information from multiple modalities, optimizing their efficiency is critical to ensuring that they can operate in real-time and provide users with accurate and timely responses. Developing algorithms that can efficiently evaluate and integrate input from several modalities is one method for improving the efficiency of multimodal NLP systems.

Overall, efficiency is a critical factor in the design of multimodal NLP systems. Researchers can increase the speed, precision, and scalability of these systems by inventing efficient algorithms, pre-processing approaches, and hardware architectures, allowing them to run successfully and offer real-time replies to consumers. Software Engineering training will help you level up your career and gear up to land you a job in the top product companies as a skilled Software Engineer.

3. Applications of Data Mining in Software Engineering

Mining Software Engineering Data

The mining of software engineering data is one of the significant research paper topics for software engineering, involving the application of data mining techniques to extract insights from enormous datasets that are generated during software development processes. The purpose of mining software engineering data is to uncover patterns, trends, and various relationships that can inform software development practices, increase software product quality, and improve software development process efficiency.

Mining software engineering data, despite its potential benefits, has various obstacles, including the quality of data, scalability, and privacy of data. Continuous research in this area is required to develop more effective data mining techniques and tools, as well as methods for ensuring data privacy and security, to address these challenges. By tackling these issues, mining software engineering data can continue to promote many positive aspects in software development practices and the overall quality of product.

Clustering and Text Mining

Clustering is a data mining approach that is used to group comparable items or data points based on their features or characteristics. Clustering can be used to detect patterns and correlations between different components of software, such as classes, methods, and modules, in the context of software engineering data.

On the other hand, text mining is a method of data mining that is used to extract valuable information from unstructured text data such as software manuals, code comments, and bug reports. Text mining can be applied in the context of software engineering data to find patterns and trends in software development processes

4. Data Modeling

Data modeling is an important area of research paper topics in software engineering study, especially in the context of the design of databases and their management. It involves developing a conceptual model of the data that a system will need to store, organize, and manage, as well as establishing the relationships between various data pieces. One important goal of data modeling in software engineering research is to make sure that the database schema precisely matches the system's and its users' requirements. Working closely with stakeholders to understand their needs and identify the data items that are most essential to them is necessary.

5. Verification and Validation

Verification and validation are significant research project ideas for software engineering research because they help us to ensure that software systems are correctly built and suit the needs of their users. While most of the time, these terms are frequently used interchangeably, they refer to distinct stages of the software development process. The process of ensuring that a software system fits its specifications and needs is referred to as verification. This involves testing the system to confirm that it behaves as planned and satisfies the functional and performance specifications. In contrast, validation is the process of ensuring that a software system fulfils the needs of its users and stakeholders.

This includes ensuring that the system serves its intended function and meets the requirements of its users. Verification and validation are key components of the software development process in software engineering research. Researchers can help to improve the functionality and dependability of software systems, minimize the chance of faults and mistakes, and ultimately develop better software products for their consumers by verifying that software systems are designed correctly and that they satisfy the needs of their users.

6. Software Project Management

Software project management is an important component of software engineering research because it comprises the planning, organization, and control of resources and activities to guarantee that software projects are finished on time, within budget, and to the needed quality standards. One of the key purposes of software project management in research is to guarantee that the project's stakeholders, such as users, clients, and sponsors, are satisfied with their needs. This includes defining the project's requirements, scope, and goals, as well as identifying potential risks and restrictions to the project's success.

7. Software Quality

The quality of a software product is defined as how well it fits in with its criteria, how well it performs its intended functions, and meets the needs of its consumers. It includes features such as dependability, usability, maintainability, effectiveness, and security, among others. Software quality is a prominent and essential research topic in software engineering. Researchers are working to provide methodologies, strategies, and tools for evaluating and improving software quality, as well as forecasting and preventing software faults and defects. Overall, software quality research is a large and interdisciplinary field that combines computer science, engineering, and statistics. Its mission is to increase the reliability, accessibility, and overall quality of software products and systems, thereby benefiting both software developers and end consumers.

8. Ontology

Ontology is a formal specification of a conception of a domain used in computer science to allow knowledge sharing and reuse. Ontology is a popular and essential area of study in the context of software engineering research. The construction of ontologies for specific domains or application areas could be a research topic in ontology for software engineering. For example, a researcher may create an ontology for the field of e-commerce to give common knowledge and terminology to software developers as well as stakeholders in that domain. The integration of several ontologies is another intriguing study topic in ontology for software engineering. As the number of ontologies generated for various domains and applications grows, there is an increasing need to integrate them in order to enable interoperability and reuse.

9. Software Models

In general, a software model acts as an abstract representation of a software system or its components. Software models can be used to help software developers, different stakeholders, and users communicate more effectively, as well as to properly evaluate, design, test, and maintain software systems. The development and evaluation of modeling languages and notations is one research example connected to software models. Researchers, for example, may evaluate the usefulness and efficiency of various modeling languages, such as UML or BPMN, for various software development activities or domains.

Researchers could also look into using software models for software testing and verification. They may investigate how models might be used to produce test cases or to do model checking, a formal technique for ensuring the correctness of software systems. They may also examine the use of models for monitoring at runtime and software system adaptation.

The Software Development Life Cycle (SDLC) is a software engineering process for planning, designing, developing, testing, and deploying software systems. SDLC is an important research issue in software engineering since it is used to manage software projects and ensure the quality of the resultant software products by software developers and project managers. The development and evaluation of novel software development processes is one SDLC-related research topic. SDLC research also includes the creation and evaluation of different software project management tools and practices.

Researchers may also check the implementation of SDLC in specific sectors or applications. They may, for example, investigate the use of SDLC in the development of systems that are more safety-critical, such as medical equipment or aviation systems, and develop new processes or tools to ensure the safety and reliability of these systems. They may also look into using SDLC to design software systems in new sectors like the Internet of Things or in blockchain technology.

Why is Software Engineering Required?

Software engineering is necessary because it gives a systematic way to developing, designing, and maintaining reliable, efficient, and scalable software. As software systems have become more complicated over time, software engineering has become a vital discipline to ensure that software is produced in a way that is fully compatible with end-user needs, reliable, and long-term maintainable.

When the cost of software development is considered, software engineering becomes even more important. Without a disciplined strategy, developing software can result in overinflated costs, delays, and a higher probability of errors that require costly adjustments later. Furthermore, software engineering can help reduce the long-term maintenance costs that occur by ensuring that software is designed to be easy to maintain and modify. This can save money in the long run by lowering the number of resources and time needed to make software changes as needed.

2. Scalability

Scalability is an essential factor in software development, especially for programs that have to manage enormous amounts of data or an increasing number of users. Software engineering provides a foundation for creating scalable software that can evolve over time. The capacity to deploy software to diverse contexts, such as cloud-based platforms or distributed systems, is another facet of scalability. Software engineering can assist in ensuring that software is built to be readily deployed and adjusted for various environments, resulting in increased flexibility and scalability.

3. Large Software

Developers can break down huge software systems into smaller, simpler parts using software engineering concepts, making the whole system easier to maintain. This can help to reduce the software's complexity and makes it easier to maintain the system over time. Furthermore, software engineering can aid in the development of large software systems in a modular fashion, with each module doing a specific function or set of functions. This makes it easier to push new features or functionality to the product without causing disruptions to the existing codebase.

4. Dynamic Nature

Developers can utilize software engineering techniques to create dynamic content that is modular and easily modifiable when user requirements change. This can enable adding new features or functionality to dynamic content easier without disturbing the existing codebase. Another factor to consider for dynamic content is security. Software engineering can assist in ensuring that dynamic content is generated in a secure manner that protects user data and information.

5. Better Quality Management

An organized method of quality management in software development is provided by software engineering. Developers may ensure that software is conceived, produced, and maintained in a way that fulfills quality requirements and provides value to users by adhering to software engineering principles. Requirement management is one component of quality management in software engineering. Testing and validation are another part of quality control in software engineering. Developers may verify that their software satisfies its requirements and is error-free by using an organized approach to testing.

In conclusion, the subject of software engineering provides a diverse set of research topics with the ability to progress the discipline while enhancing software development and maintenance procedures. This article has dived deep into various research topics in software engineering for masters and research topics for software engineering students such as software testing and validation, software security, artificial intelligence, Natural Language Processing, software project management, machine learning, Data Mining, etc. as research subjects. Software engineering researchers have an interesting chance to explore these and other research subjects and contribute to the development of creative solutions that can improve software quality, dependability, security, and scalability.

Researchers may make important contributions to the area of software engineering and help tackle some of the most serious difficulties confronting software development and maintenance by staying updated with the latest research trends and technologies. As software grows more important in business and daily life, there is a greater demand for current research topics in software engineering into new software engineering processes and techniques. Software engineering researchers can assist in shaping the future of software creation and maintenance through their research, ensuring that software stays dependable, safe, reliable and efficient in an ever-changing technological context. KnowledgeHut’s top Programming certification course will help you leverage online programming courses from expert trainers.

Frequently Asked Questions (FAQs)

Ans: To find a research topic in software engineering, you can review recent papers and conference proceedings, talk to different experts in the field, and evaluate your own interests and experience. You can use a combination of these approaches.

Ans: You should study software development processes, various programming languages and their frameworks, software testing and quality assurance, software architecture, various design patterns that are currently being used, and software project management as a software engineering student.

Ans: Empirical research, experimental research, surveys, case studies, and literature reviews are all types of research in software engineering. Each sort of study has advantages and disadvantages, and the research method chosen is determined by the research objective, resources, and available data.

Eshaan Pandey

Eshaan is a Full Stack web developer skilled in MERN stack. He is a quick learner and has the ability to adapt quickly with respect to projects and technologies assigned to him. He has also worked previously on UI/UX web projects and delivered successfully. Eshaan has worked as an SDE Intern at Frazor for a span of 2 months. He has also worked as a Technical Blog Writer at KnowledgeHut upGrad writing articles on various technical topics.

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Metric-centered and technology-independent architectural views for software comprehension

The maintenance of applications is a crucial activity in the software industry. The high cost of this process is due to the effort invested on software comprehension since, in most of cases, there is no up-to-...

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Back to the future: origins and directions of the “Agile Manifesto” – views of the originators

In 2001, seventeen professionals set up the manifesto for agile software development. They wanted to define values and basic principles for better software development. On top of being brought into focus, the ...

Investigating the effectiveness of peer code review in distributed software development based on objective and subjective data

Code review is a potential means of improving software quality. To be effective, it depends on different factors, and many have been investigated in the literature to identify the scenarios in which it adds qu...

On the benefits and challenges of using kanban in software engineering: a structured synthesis study

Kanban is increasingly being used in diverse software organizations. There is extensive research regarding its benefits and challenges in Software Engineering, reported in both primary and secondary studies. H...

Challenges on applying genetic improvement in JavaScript using a high-performance computer

Genetic Improvement is an area of Search Based Software Engineering that aims to apply evolutionary computing operators to the software source code to improve it according to one or more quality metrics. This ...

Actor’s social complexity: a proposal for managing the iStar model

Complex systems are inherent to modern society, in which individuals, organizations, and computational elements relate with each other to achieve a predefined purpose, which transcends individual goals. In thi...

Investigating measures for applying statistical process control in software organizations

The growing interest in improving software processes has led organizations to aim for high maturity, where statistical process control (SPC) is required. SPC makes it possible to analyze process behavior, pred...

An approach for applying Test-Driven Development (TDD) in the development of randomized algorithms

TDD is a technique traditionally applied in applications with deterministic algorithms, in which the input and the expected result are known. However, the application of TDD with randomized algorithms have bee...

Supporting governance of mobile application developers from mining and analyzing technical questions in stack overflow

There is a need to improve the direct communication between large organizations that maintain mobile platforms (e.g. Apple, Google, and Microsoft) and third-party developers to solve technical questions that e...

Working software over comprehensive documentation – Rationales of agile teams for artefacts usage

Agile software development (ASD) promotes working software over comprehensive documentation. Still, recent research has shown agile teams to use quite a number of artefacts. Whereas some artefacts may be adopt...

Development as a journey: factors supporting the adoption and use of software frameworks

From the point of view of the software framework owner, attracting new and supporting existing application developers is crucial for the long-term success of the framework. This mixed-methods study explores th...

Applying user-centered techniques to analyze and design a mobile application

Techniques that help in understanding and designing user needs are increasingly being used in Software Engineering to improve the acceptance of applications. Among these techniques we can cite personas, scenar...

A measurement model to analyze the effect of agile enterprise architecture on geographically distributed agile development

Efficient and effective communication (active communication) among stakeholders is thought to be central to agile development. However, in geographically distributed agile development (GDAD) environments, it c...

A survey of search-based refactoring for software maintenance

This survey reviews published materials related to the specific area of Search-Based Software Engineering that concerns software maintenance and, in particular, refactoring. The survey aims to give a comprehen...

Guest editorial foreword for the special issue on automated software testing: trends and evidence

Similarity testing for role-based access control systems.

Access control systems demand rigorous verification and validation approaches, otherwise, they can end up with security breaches. Finite state machines based testing has been successfully applied to RBAC syste...

An algorithm for combinatorial interaction testing: definitions and rigorous evaluations

Combinatorial Interaction Testing (CIT) approaches have drawn attention of the software testing community to generate sets of smaller, efficient, and effective test cases where they have been successful in det...

How diverse is your team? Investigating gender and nationality diversity in GitHub teams

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Investigating factors that affect the human perception on god class detection: an analysis based on a family of four controlled experiments

Evaluation of design problems in object oriented systems, which we call code smells, is mostly a human-based task. Several studies have investigated the impact of code smells in practice. Studies focusing on h...

On the evaluation of code smells and detection tools

Code smells refer to any symptom in the source code of a program that possibly indicates a deeper problem, hindering software maintenance and evolution. Detection of code smells is challenging for developers a...

On the influence of program constructs on bug localization effectiveness

Software projects often reach hundreds or thousands of files. Therefore, manually searching for code elements that should be changed to fix a failure is a difficult task. Static bug localization techniques pro...

DyeVC: an approach for monitoring and visualizing distributed repositories

Software development using distributed version control systems has become more frequent recently. Such systems bring more flexibility, but also greater complexity to manage and monitor multiple existing reposi...

A genetic algorithm based framework for software effort prediction

Several prediction models have been proposed in the literature using different techniques obtaining different results in different contexts. The need for accurate effort predictions for projects is one of the ...

Elaboration of software requirements documents by means of patterns instantiation

Studies show that problems associated with the requirements specifications are widely recognized for affecting software quality and impacting effectiveness of its development process. The reuse of knowledge ob...

ArchReco: a software tool to assist software design based on context aware recommendations of design patterns

This work describes the design, development and evaluation of a software Prototype, named ArchReco, an educational tool that employs two types of Context-aware Recommendations of Design Patterns, to support us...

On multi-language software development, cross-language links and accompanying tools: a survey of professional software developers

Non-trivial software systems are written using multiple (programming) languages, which are connected by cross-language links. The existence of such links may lead to various problems during software developmen...

SoftCoDeR approach: promoting Software Engineering Academia-Industry partnership using CMD, DSR and ESE

The Academia-Industry partnership has been increasingly encouraged in the software development field. The main focus of the initiatives is driven by the collaborative work where the scientific research work me...

Issues on developing interoperable cloud applications: definitions, concepts, approaches, requirements, characteristics and evaluation models

Among research opportunities in software engineering for cloud computing model, interoperability stands out. We found that the dynamic nature of cloud technologies and the battle for market domination make clo...

Game development software engineering process life cycle: a systematic review

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Correlating automatic static analysis and mutation testing: towards incremental strategies

Traditionally, mutation testing is used as test set generation and/or test evaluation criteria once it is considered a good fault model. This paper uses mutation testing for evaluating an automated static anal...

A multi-objective test data generation approach for mutation testing of feature models

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An extended global software engineering taxonomy

In Global Software Engineering (GSE), the need for a common terminology and knowledge classification has been identified to facilitate the sharing and combination of knowledge by GSE researchers and practition...

A systematic process for obtaining the behavior of context-sensitive systems

Context-sensitive systems use contextual information in order to adapt to the user’s current needs or requirements failure. Therefore, they need to dynamically adapt their behavior. It is of paramount importan...

Distinguishing extended finite state machine configurations using predicate abstraction

Extended Finite State Machines (EFSMs) provide a powerful model for the derivation of functional tests for software systems and protocols. Many EFSM based testing problems, such as mutation testing, fault diag...

Extending statecharts to model system interactions

Statecharts are diagrams comprised of visual elements that can improve the modeling of reactive system behaviors. They extend conventional state diagrams with the notions of hierarchy, concurrency and communic...

On the relationship of code-anomaly agglomerations and architectural problems

Several projects have been discontinued in the history of the software industry due to the presence of software architecture problems. The identification of such problems in source code is often required in re...

An approach based on feature models and quality criteria for adapting component-based systems

Feature modeling has been widely used in domain engineering for the development and configuration of software product lines. A feature model represents the set of possible products or configurations to apply i...

Patch rejection in Firefox: negative reviews, backouts, and issue reopening

Writing patches to fix bugs or implement new features is an important software development task, as it contributes to raise the quality of a software system. Not all patches are accepted in the first attempt, ...

Investigating probabilistic sampling approaches for large-scale surveys in software engineering

Establishing representative samples for Software Engineering surveys is still considered a challenge. Specialized literature often presents limitations on interpreting surveys’ results, mainly due to the use o...

Characterising the state of the practice in software testing through a TMMi-based process

The software testing phase, despite its importance, is usually compromised by the lack of planning and resources in industry. This can risk the quality of the derived products. The identification of mandatory ...

Self-adaptation by coordination-targeted reconfigurations

A software system is self-adaptive when it is able to dynamically and autonomously respond to changes detected either in its internal components or in its deployment environment. This response is expected to ensu...

Templates for textual use cases of software product lines: results from a systematic mapping study and a controlled experiment

Use case templates can be used to describe functional requirements of a Software Product Line. However, to the best of our knowledge, no efforts have been made to collect and summarize these existing templates...

F3T: a tool to support the F3 approach on the development and reuse of frameworks

Frameworks are used to enhance the quality of applications and the productivity of the development process, since applications may be designed and implemented by reusing framework classes. However, frameworks ...

NextBug: a Bugzilla extension for recommending similar bugs

Due to the characteristics of the maintenance process followed in open source systems, developers are usually overwhelmed with a great amount of bugs. For instance, in 2012, approximately 7,600 bugs/month were...

Assessing the benefits of search-based approaches when designing self-adaptive systems: a controlled experiment

The well-orchestrated use of distilled experience, domain-specific knowledge, and well-informed trade-off decisions is imperative if we are to design effective architectures for complex software-intensive syst...

Revealing influence of model structure and test case profile on the prioritization of test cases in the context of model-based testing

Test case prioritization techniques aim at defining an order of test cases that favor the achievement of a goal during test execution, such as revealing failures as earlier as possible. A number of techniques ...

A metrics suite for JUnit test code: a multiple case study on open source software

The code of JUnit test cases is commonly used to characterize software testing effort. Different metrics have been proposed in literature to measure various perspectives of the size of JUnit test cases. Unfort...

Designing fault-tolerant SOA based on design diversity

Over recent years, software developers have been evaluating the benefits of both Service-Oriented Architecture (SOA) and software fault tolerance techniques based on design diversity. This is achieved by creat...

Method-level code clone detection through LWH (Light Weight Hybrid) approach

Many researchers have investigated different techniques to automatically detect duplicate code in programs exceeding thousand lines of code. These techniques have limitations in finding either the structural o...

The problem of conceptualization in god class detection: agreement, strategies and decision drivers

The concept of code smells is widespread in Software Engineering. Despite the empirical studies addressing the topic, the set of context-dependent issues that impacts the human perception of what is a code sme...

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150 Best Research Paper Topics For Software Engineering

Software Engineering is a branch which deals with the creation and improvement of software applications using specific methodologies and clearly defined scientific principles. When developing software products, certain procedures must be followed, the outcome of which is a reliable and reliable software product. Software is a collection of executable code for programs with associated libraries. Software that is designed to meet certain requirements is referred to as a Software Product . This is an excellent subject for a master's thesis, research, or project. There are a variety of topics within Software Engineering which will be useful to M.Tech and other students studying for their masters to write their software thesis.

What is the reason Software Engineering is required?

Software Engineering is necessary due to the frequent shifts in the requirements of users as well as the environment. Through yourch and thesis, you will learn more about the significance of Software Engineering. Here are some other areas in software engineering that are needed:

Big Software: The massive dimension of software makes it necessary for the requirements in software engineering .
Scalability The concept of scaling Software Engineering makes it possible to increase the size of existing software rather than develop brand-new software.
Cost Price Software Engineering also cuts down the manufacturing cost that is incurred during software development.
The dynamic nature of Software - Software Engineering is a crucial factor when the need for new features is to be made in software in place, in the event that the nature of software is fluid.
Better Quality Management - Software Engineering can provide more efficient software development processes to provide superior-high-quality services .

Best Research Paper Topics on Software

Software Engineering Management Unified Software Development Process and Extreme ProgrammingThere are a lot of difficulties with managing the development of software for web-based applications and projects for systems integration that were completed in recent times.
The Blue Sky Software Consulting Company Analysis
Blue Sky Software Consulting Blue Sky Software Consulting company has seen great success over 15 years. The company is not as well-equipped for the current market.
LabVIEW Software: Design Systems of Measurement
LabVIEW is a software program that was created to design systems for measurement. LabVIEW gives you a range of instruments to control the process in an experiment.
Software-producing Firm Reducing Inventory
The link between the reduction in inventory levels and the number of orders is evident. An organization that produces software may think of increasing the amount of software to a lower level.
Moet Hennessy - Louis Vuitton: Enterprise Software
The report will demonstrate how the introduction of ERP will help LVHM Group improve its results by improving its inventories, logistics and accounting.
Virtualization and Software-Defined Networking
The goal of this paper is to analyze the developments in the field of virtualization, software-defined networks and security for networks in the last three years.
Computer Hardware and Software Components
Computers that were developed at the time of the 40s of 1940 have evolved into complex machines that require software and hardware for their operation.
Applications, Software and System Development
The usage the Microsoft Office applications greatly enhance productivity in the classroom as well as at work and during everyday activities at home.
PeopleSoft Inc.'s Software Architecture and Design
With the PIA architecture, any company with an ERP application can access all of its operations through a Web browser.
Co-operative Banking Group's Enterprise Software
The report demonstrates how the implementation of the ERP system within the Co-operative Banking Group will help in improving the company's accounting, inventory and accounting practices as well as logistics processes.
Software Testing: Manual and Automated Web-Application Testing Tools
This research is an empirical study of automated and manual web-based application testing tools to determine the best tool for testing software.
JDA Software Company's Services
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Data Management, Networking and Enterprise Software
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Software Workshops and Seminars Reflections
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The Various Enterprise Resource Planning Software Packages
This paper's purpose is to provide an overview of the various Enterprise Resource Planning (ERP) software applications that are widely employed by companies to manage their business operations.
Explore Factors in IBM SPSS Statistical Software
The "Explore" or "Explore" command in IBM SPSS generates an output with a variety of stats for a single variable, across the entire sample or in sections of the sample.
Split Variables in IBM SPSS Statistical Software
It is the IBM SPSS software provides an option to split files into groups. The members of cases within groups can be determined by the values of split variables in this particular instance.
Syntax Code Writing in Statistical Software
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Data Coding in Statistical Software
Data coding is of utmost importance when a proper analysis of this data has to be conducted. Data coding plays an important function when you need to make use of statistical software.
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Software piracy is a pressing current issue that is manifested both locally with respect to an individual company and also globally.
Hotjar: Web Analytics Software Difference
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Avast Software: Company Analysis
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Project Failure, Project Planning Fundamentals, and Software Tools and Techniques for Alternative Scheduling
From lack of communication to generally unfavourable working conditions, Projects may fail when managers fail to prepare for their implementation.
Computer Elements such as Hardware and Software
Personal computers are usually different from computers used for business in terms of capabilities and the extent of technology used within the equipment.
Review of a New Framework for Software Reliability Measurement
This study draws upon the in-depth study of the software reliability measurement methods and the suggestion of a fresh foundation for reliability measurement built on the software metrics studied in the work of Amar as well as Rabai.

Good Software Research Topics & Essay Examples

Task Management Software in Organization
The goal of the plan for managing projects is to present the process of creating task management software that can be integrated into the context of the company.
A task management software plan's risk management strategy
The present study introduces us to the techniques for risk identification as well as quality assurance and a control plan and explains their significance.
Computer Software Development and Reality Shows
The growth of software in computers has been at such a fast rate over the last 10 years that it has impacted all aspects of our lives and every fibre of our being.
Scrum - Software Development Process
Digital systems and computerized systems have brought life to many areas. Scrum is a process for software development that guarantees high quality and efficiency.
Distribution of Anti-Virus Software
Numerous new threats are reported every fortnight. Cyberattacks, viruses, and other cyber-related threats are becoming an issue.
Marketing Plan: Innovative Type of Software Product
This paper will create an advertisement plan for the new kind of software, which will help to define the segment of clients and the price and communications platform.
Marketing System of Sakhr Software Co
The principal objective of this paper is to examine the marketing process in the same type of organization, like Sakhr Software Co.
Managing Information of Sakhr Software Co
This paper will examine the ideas of managing information for Sakhr Software, which is a well-known language software firm.
CRM Software in Amazon: Gains
The software for managing customers that Amazon.com developed is, from the beginning, one of the latest technology.
Neurofeedback Software and Technology Comparison
MIDI technology helps make the making of, learning or playing more enjoyable. Mobile phones and computer keyboards for music, computers etc., utilize MIDI.
PeopleSoft Software and HR.net Enterprise Software
With the help of HRIS software, HR employees are able to manage their own benefits updates and make changes, allowing them to take more time to focus on other important tasks.
Business Applications: Revelation HelpDesk by Yellow Fish Software
"Revelation HelpDesk" is an online Tracking and Support Software that facilitates seamless coordination to occur between the most important divisions within an organization.
3D signal editing methods and editing software for stereoscopic movies
3D editing for movies is one of the newest trends and is among the most complex processes in the modern film industry.
ERP Software in Inventory Management
Management of inventory ERP applications will be useful when a business has to manage the manner in which it gets goods and cleans up the merchandise.
The Capabilities of Compiere Software and How Well It Fits Into Different Industries
It is the ERP software Compiere can be used by a wide variety of users, including governments, businesses as well as non-governmental organizations (NGOs).
Software Tools for Qualitative Research
This paper reviews software tools to solve complicated tasks in the analysis of data. The paper compares NVivo, HyperRESEARCH, and Dedoose.
Data Scientist and Software Development
Data scientists convert data into insights, giving elaborate guidance to those who use the data to make educated decisions and take action.
IPR Violations in Software Development
The copyright law protects only the declaration but not the software concept. It prohibits copying code from the source without asking permission.
Health IT: Epic Software Analysis
Implementation and adoption of Health IT systems are crucial to improve the efficiency of medical practices, efficiency of workflow as well as patient outcomes.
Agile Software Development Process
The agile process for software development offers numerous benefits, such as the speedy and continuous execution of your project.
Project Management Software and Tools Comparison
The software is used by managers to ensure that there isn't any worker who is receiving more work than others and also to ensure that no worker is falling behind in their job.
Visually impaired people: challenges in Assistive Technology Software
Blind people suffer from a number of disadvantages each day while using digital technology. The various types of software and software discussed in this paper have been specifically designed to help improve the lives of blind people.
WBS completion and software project management
The PERT's results resulted in the development of The Gantt chart. This essay provides an account of the method of working with the Gantt chart.
International Software Development's Ethical Challenges: User-Useful Software
The importance of ethics is when it comes to software development. It helps the creator to create software that will be useful for the user as well as the management.
Achieving the Optimal Process. Software Development
The industry of software development is growing rapidly as the requirements of users change. This requires applications to meet these needs.

Innovative Software to Blog About

System Software: Analysis of Various Types of System Software
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Sakhr Software Co.'s Marketing System
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Program Code in Assembly Language Using Easy68K Software
A typical scenario is described in the report to write program code in assembly language with Easy68K software. The appropriate tests were carried out with success and outputs.
Benefits and Drawbacks of Agile Software Development Techniques
The use of agile methodologies in the software development process contributes to the improvement of work as well as the effectiveness of performance.
The use of agile methodologies in the development of software contributes to the efficiency of work and efficiency of performance.
Large Scale Software Development
This report gives information on this Resource Scheduling project. It can be useful to an advisory firm that offers various types of resources.
Penguin Sleuth, a Forensic Software Tool
The primary goal of this paper is to examine the various tools for forensic analysis and also provide a comprehensive overview of the functions available for each tool or tool pack.
System Software: Computer System Management
Computer software comprises precise preprogrammed instructions that regulate and coordinate hardware components of the computer.
Ethical Issues Involved in Software Project Management
Ethics within IT have been proven to be very different from other areas of ethics. Ethics issues in IT are usually described as having little.
Advantages and Disadvantages of Software Suites
Computer software comprises specific preprogrammed commands that control and coordinate computer hardware components of an info system.
Descriptive Statistics Using SPSS Software Suite
This paper focuses on the process of producing the descriptive statistical analysis by using SPSS. The purpose of this article is to make use of SPSS to perform an analysis of descriptive data.
Software Development: Creating a Prototype
The aim of this article is to develop an experimental software program that can be utilized to aid breast cancer patients.
Software Engineering and Methodologies
The paper explains how the author learned the software engineering process and methods as an outcome of his experiences at BTR IT Consulting Company.
Information System Hardware and Software
Information technology covers a wide variety of applications in which computer software, along with hardware, is employed.
Software Development Project Using Agile Methods
The report will provide reasons behind why the agile methodology was chosen, the method used, how the team applied this methodology, and also the lessons learned from the massive project of software development.
Flight Planning Software and Aircraft Incidents
Software for flight planning refers to programs utilized to control and manage flights and other procedures while the plane is in flight.
Hardware and Software Systems and Criminal Justice
One of the primary techniques used to decrease the chance of criminal activity is crime mapping. This involves collecting information on crimes and their causes and then analyzing it in order to identify issues.
Why Open-Source Software Will (Or Will Not) Soon Dominate the Field of Database Management Tools
The research aims to determine whether open-source software will rule the field of the database since there is an evolution in the market for business.
Business HRM Software and the Affordable Care Act
The Affordable Care Act has its strengths but also flaws. The reason is the complex nature of the law that creates a variety of challenges.
Antivirus Software Ensuring Security Online
Although it's not perfect and fragmentary, it can be seen as a supplement and not the sole instrument; antivirus software will help protect one's privacy online.
Evaluating Teaching Instructional Software for 21st-Century Technology Resources
The software for teaching Joe Rock and Friends Book 2 is designed for third-grade students who are studying English as an additional language to read and learn new vocabulary.
Britam Insurance Company's Sales and Marketing Management Software
Britam Insurance Company needs to implement the latest marketing and management software in order to keep its place at the forefront of the extremely competitive insurance market.
Software Programs: Adobe Illustrator
With Adobe Illustrator, users can quickly and precisely create various products, like logos, icons as well as drawings.
Strawberry Business: Software Project Management
Although the company has an established management strategy as well as a team of employees and efficient information systems, it lacks a standardized workplace culture and customer relations systems.
Value of Salesforce Software Using VRIO Model
Salesforce CRM software is created to help managers manage their businesses effectively. It connects all teams and managers and collects and manages customer information.
Agile software development, as well as popular variations like Scrum, are the foundation for the work of a variety of testers and developers. No matter what team or method you're currently using, you can get expert guidance on process structure and the skills required to use Lean, Agile, DevOps, Waterfall and more to help you implement it for your business.

Most Interesting Software Research Titles

What Are the Essential Attributes of Good Software?
How Computer Software Can Be Used as a Tool for Education
Accounting Software and Application Software
Online National Polling Software Requirements Specification
Building Their Software for a Company's Success
The Role of Antivirus Software in Protecting Your Computer Data
Intellectual Property Rights, Innovation and Software Technologies
Software Piracy and the Canadian Piracy Act
For the development of software projects, agile methodologies and their Waterscrumfall derivative are used.
Software Tools for Improving Underground Mine Access Layouts
How Software Can Support Academic Librarians' Changing Role
Using the Untangle Software to Overcome Obstacles for Small Businesses
By employing travel portal software, online booking sales will increase.
Analysis of Network Externality and Commercial Software Piracy
Accounting Software and Business Solutions
Analysis of Key Issues and Effects Relating to International Software Piracy
The Distinction Between Computer Science and Software Engineering
Modulation: Computer Software and Unknown Music Virus
Math Software for High School Students with Disabilities
Keyboarding Software Packages: Analysis and Purchase Recommended
Basic Software Development Life Cycle
India's Problems with Software Patents, Copyright, and Piracy
Why Has India Been Able to Build a Thriving Software Industry
Does Social Software Increase Labour Productivity
The Role of Open Source Software for Database Servers

Simple Software Essay Ideas

Human Capital and the Indian Software Industry
Input-Output Computer Windows Software
Business Software Development and Its Implementation
Evaluating Financial Management Software: Quicken Software
Which governance tools are important in Africa for combating software piracy?
Distinguish Between Proprietary Software and Off-The-Shelf
Does Social Software Support Service Innovation
Ambulatory Revenue Management Software
Difference Between Operating Systems and Application Software
Leading a Global Insurgency in the Software Sector are China and India
Call Accounting Software for Every Enterprise
Technology Standards for Software Outsourcing
The Importance of the Agile Approach for Software Development
Application Software: Publisher, Word, and Excel
Employee Monitoring Through Computer Software
Software Development Lifecycle and Testing's Importance
Tools for Global Conditional Policy to Combat Software Piracy
Software for Designing Solar Water Heating Systems
Open Source Software, Competition, and Potential Entry
Indian Software Industry: Gains are distorted and consolidated
Software Programs for Disabled Computer Users and Assistive Technology
Agile Software Architecture, Written by Christine Miyachi
Software Development: The Disadvantages of Agile Methods
Computer Software Technology for Early Childhood
Developing Test Automation Software Development

Easy Software Essay Topics

Growth Trends, Barriers, and Government Initiatives in the Indian Software Industry
How Does Enterprise Software Enable a Business to Use
Integrated Management Software the Processing of Information
Computer Software Training for Doctor's Office
Software Intellectual Property Rights and Venture Capitalist Access
Computer Science Software Specification
Software Projects and Student Software Risk Exposure
Why It Is Difficult to Create Software for Wireless Devices
Affiliate Tracking Software Your Payment Options
How Can Volkswagen Recover From the Cheating Issues It Had Because Illegal Software Was Installed?
Principles of Best Forensic Software Tool
The American Software Industry: A Historical Analysis
How Peripheral Developers Contribute to the Development of Open-Source Software
Agile Methodologies for Software Development
Key Macroeconomic Factors That Affect Software Industry
The Software Industry and India's Economic Development
Improving Customer Service Through Help Desk Software
Enterprise Resource Planning and Sap Software
Antivirus Software and Its Importance
Hardware and Software Used in Public Bank
The Effects of Computer Software Piracy on the Global Economy
Using the Winqsb Software in Critical Path Analysis
General Information About Interactive Multimedia-Based Educational Software
How Affiliate Tracking Software Can Benefit You
Computer Software and Recent Technologies

Frequently asked questions

What are the main topics of software engineering .

software development.

Introduction
Models and architecture for software development
Project management for software (SPM)
Software prerequisites
Testing and debugging software

What makes good research in software engineering ?

The most typical research strategy in software engineering is coming up with a novel method or methodology, validating it through analysis, or demonstrating its application through a case study;

What projects are good for software engineering ?

monitoring of Android tasks.
Analyzing attitudes to rate products
ATM with a fingerprint-based method.
a modern system for managing employees.
Using the AES technique for image encryption.
vote-by-fingerprint technology.
system for predicting the weather

What are the research methods in software engineering ?

We list and contrast the five categories of research methodology that, in our opinion, are most pertinent to software engineering: controlled experiments (including quasi-experiments); case studies (both exploratory and confirmatory); survey research; ethnographies; action research; and controlled experiments.

Is software engineering a research area ?

A relatively recent area of research, software engineering is derived from computer science. Its significance has been generally acknowledged by more and more academics in the field of computers throughout the course of six decades, from 1948 to the present, and it has developed into a vibrant and promising division of the computing profession.

Is software engineering easy ?

Yes, learning software engineering can be challenging at first, especially for those without programming or coding experience or any background in technology. However, numerous courses, tools, and other resources are available to assist with learning how to become a software engineer.

Who is the father of software engineering ?

The "father of software quality," Watts S. Humphrey, was an American software engineering pioneer who lived in Battle Creek, Michigan (U.S.) from July 4, 1927, to October 28, 2010.

What do you do in software engineering ?

roles and tasks for software engineers
creating and keeping up software systems.
testing and evaluating new software applications.
software speed and scalability optimization.
code creation and testing.
consulting with stakeholders such as clients, engineers, security experts, and others.

Which is better it or software engineering ?

IT support engineers cannot build sophisticated solutions, while software engineers can. In a word, they are in charge of creating and putting into use software. Knowing the distinctions makes it easier to choose the right individual to handle our tech-related problems.

Are junior software engineers in demand ?

Yes, there is a need for young coders.

Is software engineering going down ?

Software experts and software goods are oversaturating the job market for software engineers.

What degree do I need to be a software engineer ?

undergraduate degree

Can I be a software engineer without a degree ?

Many software developers lack a degree from a reputable university (or, in some circumstances, none at all).

How many years can a software engineer work ?

An engineer who wants to work in IT has a 15–20 year window.

How many hours do software engineers work ?

Software developers put in 8 to 9 hours each day, or 40 to 45 hours per week.

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Software Engineering

At Google, we pride ourselves on our ability to develop and launch new products and features at a very fast pace. This is made possible in part by our world-class engineers, but our approach to software development enables us to balance speed and quality, and is integral to our success. Our obsession for speed and scale is evident in our developer infrastructure and tools. Developers across the world continually write, build, test and release code in multiple programming languages like C++, Java, Python, Javascript and others, and the Engineering Tools team, for example, is challenged to keep this development ecosystem running smoothly. Our engineers leverage these tools and infrastructure to produce clean code and keep software development running at an ever-increasing scale. In our publications, we share associated technical challenges and lessons learned along the way.

Recent Publications

Some of our teams.

Climate and sustainability

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We're always looking for more talented, passionate people.

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Cite this post.

AMS Citation

Carleton, A., 2021: Architecting the Future of Software Engineering: A Research and Development Roadmap. Carnegie Mellon University, Software Engineering Institute's Insights (blog), Accessed April 2, 2024, https://insights.sei.cmu.edu/blog/architecting-the-future-of-software-engineering-a-research-and-development-roadmap/.

APA Citation

Carleton, A. (2021, July 12). Architecting the Future of Software Engineering: A Research and Development Roadmap. Retrieved April 2, 2024, from https://insights.sei.cmu.edu/blog/architecting-the-future-of-software-engineering-a-research-and-development-roadmap/.

Chicago Citation

Carleton, Anita. "Architecting the Future of Software Engineering: A Research and Development Roadmap." Carnegie Mellon University, Software Engineering Institute's Insights (blog) . Carnegie Mellon's Software Engineering Institute, July 12, 2021. https://insights.sei.cmu.edu/blog/architecting-the-future-of-software-engineering-a-research-and-development-roadmap/.

IEEE Citation

A. Carleton, "Architecting the Future of Software Engineering: A Research and Development Roadmap," Carnegie Mellon University, Software Engineering Institute's Insights (blog) . Carnegie Mellon's Software Engineering Institute, 12-Jul-2021 [Online]. Available: https://insights.sei.cmu.edu/blog/architecting-the-future-of-software-engineering-a-research-and-development-roadmap/. [Accessed: 2-Apr-2024].

BibTeX Code

@misc{carleton_2021, author={Carleton, Anita}, title={Architecting the Future of Software Engineering: A Research and Development Roadmap}, month={Jul}, year={2021}, howpublished={Carnegie Mellon University, Software Engineering Institute's Insights (blog)}, url={https://insights.sei.cmu.edu/blog/architecting-the-future-of-software-engineering-a-research-and-development-roadmap/}, note={Accessed: 2024-Apr-2} }

Architecting the Future of Software Engineering: A Research and Development Roadmap

Anita Carleton

July 12, 2021, published in.

Software Engineering Research and Development

This post has been shared 10 times.

This post is coauthored by John Robert, Mark Klein, Doug Schmidt, Forrest Shull, John Foreman, Ipek Ozkaya, Robert Cunningham, Charlie Holland, Erin Harper, and Edward Desautels

Software is vital to our country’s global competitiveness, innovation, and national security. It also ensures our modern standard of living and enables continued advances in defense, infrastructure, healthcare, commerce, education, and entertainment. As the DoD’s federally funded research and development center (FFRDC) focused on improving the practice of software engineering, the Carnegie Mellon University (CMU) Software Engineering Institute (SEI) is leading the community in creating a multi-year research and development vision and roadmap for engineering next-generation software-reliant systems. This blog post describes that effort.

Software Engineering as Strategic Advantage

In a 2020 National Academy of Science Study on Air Force software sustainment , the U.S. Air Force recognized that “to continue to be a world-class fighting force, it needs to be a world-class software developer.” This concept clearly applies far beyond the Department of Defense . Software systems enable world-class healthcare, commerce, education, energy generation, and more. These systems that run our world are rapidly becoming more data intensive and interconnected, increasingly utilize AI, require larger-scale integration, and must be considerably more resilient. Consequently, significant investment in software engineering R&D is needed now to enable and ensure future capability.

Goals of This Work

The SEI has leveraged its connections with academic institutions and communities, DoD leaders and members of the Defense Industrial Base , and industry innovators and research organizations to:

identify future challenges in engineering software-reliant and intelligent systems in emerging, national-priority technical domains, including gaps between current engineering techniques and future domains that will be more reliant on continuous evolution and AI
develop a research roadmap that will drive advances in foundational software engineering principles across a range of system types, such as intelligent, safety-critical, and data-intensive systems
raise the visibility of software to the point where it receives the sustained recognition commensurate with its importance to national security and competitiveness
enable strategic partnerships and collaborations to drive innovation among industry, academia, and government.

Guided by an Advisory Board of U.S. Visionaries and Senior Thought Leaders

To succeed in developing our vision and roadmap for software engineering research and development, it is vital to coordinate the academic, defense, and commercial communities to define an effective agenda and implement impactful results. To help represent the views of all these software engineering constituencies, the SEI formed an advisory board from DoD, industry, academia, research labs, and technology companies to offer guidance. Members of this advisory board include the following:

Deb Frincke , advisory board chair, Associate Laboratory Director for National Security Sciences, Oak Ridge National Laboratory
Michael McQuade , vice president for research, Carnegie Mellon University
Vint Cerf , vice president and chief internet evangelist, Google
Penny Compton , vice president for software systems, cyber, and operations, Lockheed Martin Space
Tim Dare , deputy director for prototyping and software, Office of the Under Secretary of Defense for Research and Engineering (previous position)
Sara Manning Dawson , chief technology officer enterprise security, Microsoft
Jeff Dexter , senior director of flight software & cybersecurity, SPACEX
Yolanda Gil, president, Association for the Advancement of Artificial Intelligence (AAAI); Director of Knowledge Technologies, Information Sciences Institute at University of Southern California
Tim McBride , president, Zoic Studios
Nancy Pendleton , vice president and senior chief engineer for mission systems, payloads and sensors, Boeing Defense, Space and Security
William Scherlis , director Information Innovation Office, DARPA

In June 2020, the SEI assembled this board to leverage their diverse perspectives and provide strategic advice, influence stakeholders, develop connections, assist in executing the roadmap, and advocate for the use of our results.

Future Systems and Fundamental Shifts in Software Engineering Require New Research Focus

Rapidly deploying software with confidence requires fundamental shifts in software engineering. New types of systems will continue to push beyond the bounds of what current software engineering theories, tools, and practices can support, including (but not limited to):

Systems that fuse data at a huge scale, whether for news, entertainment, or intelligence: We will need to continuously mine vast amounts of open-source data streams (e.g., YouTube videos and Twitter feeds) for important information that will in turn drive decision making. This vast stream of data will also drive new ways of constructing systems.
Smart cities, buildings, roads, cars, and transport: How will these highly connected systems work together seamlessly? How will we enable safe and affordable transportation and living?
Personal digital assistants: How will these assistants learn, adapt, and engage in home and business workflows?
Dynamically integrated healthcare: Data from your personal device will be combined with hospital data. How do we meet stringent safety and privacy requirements? How do we evaluate assurance in a highly data-driven environment?
Mission-level adaptation for DoD systems: DoD systems will feature mission-level construction of new integrated systems that combine a range of capabilities, such as intel, weapons, and human/machine teaming. The DoD is already moving in this direction, but how can we increase confidence that there will be no unintended consequences?

A Guiding Vision of the Future of Software Engineering

Our guiding vision is one in which the current notion of software development is replaced by the concept of a software pipeline consisting of humans and software as trustworthy collaborators who rapidly evolve systems based on user intent. To achieve this vision, we anticipate the need for not only new development paradigms but also new architectural paradigms for engineering new kinds of systems.

Advanced development paradigms, such as those listed below, lead to efficiency and trust at scale:

Humans leverage trusted AI as a workforce multiplier for all aspects of software creation.
Formal assurance arguments are evolved to assure and efficiently re-assure continuously evolving software.
Advanced software composition mechanisms enable predictable construction of systems at increasingly large scale.

Advanced architectural paradigms, as outlined below, enable the predictable use of new computational models:

Theories and techniques drawn from the behavioral sciences are used to design large-scale socio-technical systems, leading to predictable social outcomes.
New analysis and design methods facilitate the development of quantum-enabled systems.

AI and non-AI components interact in predictable ways to achieve enhanced mission, societal, and business goals.

Research Focus Areas

The fundamental shifts and needed advances in software engineering described above require new areas of research. In close collaboration with our advisory board and other leaders in the software engineering community, we have developed a research roadmap with six focus areas. Figure 1 shows those areas and outlines a suggested course of research topics to undertake. Short descriptions of each focus area and its challenges follow.

AI-Augmented Software Development . At almost every stage of the software development process, AI holds the promise of assisting humans. By relieving humans of tedious tasks, they will be better able to focus on tasks that require the creativity and innovation that only humans can provide. To reach this goal, we need to re-envision the entire software development process with increased AI and automation tool support for developers, and we need to ensure we take advantage of the data generated throughout the entire lifecycle. The focus of this research area is on what AI-augmented software development will look like at each stage of the development process and during continuous evolution, where it will be particularly useful in taking on routine tasks.
Assuring Continuously Evolving Systems . When we consider the software-reliant systems of today, we see that they are not static (or even infrequently updated) engineering artifacts. Instead, they are fluid—meaning that they are expected to undergo continuing updates and improvements throughout their lifespan. The goal of this research area is therefore to develop a theory and practice of rapid and assured software evolution that enables efficient and bounded re-assurance of continuously evolving systems.
Software Construction through Compositional Correctness . As the scope and scale of software-reliant systems continues to grow and change continuously, the complexity of these systems makes it unrealistic for any one person or group to understand the entire system. It is therefore necessary to integrate (and continually re-integrate) software-reliant systems using technologies and platforms that support the composition of modular components, many of which are reused from existing elements that were not designed to be integrated or evolved together. The goal of this research area is to create methods and tools (such as domain specific modeling language and annotation-based dependency injection) that enable the specification and enforcement of composition rules that allow (1) the creation of required behaviors (both functionality and quality attributes) and (2) the assurance of these behaviors.
Engineering Socio-Technical Systems . Societal-scale software systems, such as today’s commercial social media systems, are designed to keep users engaged to influence them. However, avoiding bias and ensuring the accuracy of information are not always goals or outcomes of these systems. Engineering societal-scale systems focuses on prediction of such outcomes (which we refer to as socially inspired quality attributes) that arise when we humans as integral components of the system. The goal is to leverage insights from the social sciences to build and evolve societal-scale software systems that consider qualities such as bias and influence.
Engineering AI-enabled Software Systems . AI-enabled systems, which are software-reliant systems that include AI and non-AI components, have some inherently different characteristics than those without AI. However, AI-enabled systems are, above all, a type of software system. These systems have many parallels with the development and sustainment of more conventional software-reliant systems. This research area focuses on exploring which existing software engineering practices can reliably support the development of AI systems, as well as identifying and augmenting software engineering techniques for the specification, design, architecture, analysis, deployment, and sustainment of systems with AI components.
Engineering Quantum Computing Systems . Advances in software engineering for quantum are as important as the hardware advances. The goals of this research area are to first enable current quantum computers so they can be programmed more easily and reliably, and then enable increasing abstraction as larger, fully fault-tolerant quantum computing systems become available. Eventually, it should be possible fully integrate these types of systems into a unified classical and quantum software development lifecycle.

Help Shape Our National Software Research Agenda

Along with the advisory board, our research team has examined future trends in the computing landscape and emerging technologies; conducted a series of expert interviews; and convened multiple workshops for broad engagement and diverse perspectives, including a workshop on Software Engineering Grand Challenges and Future Visions co-hosted with the Defense Advanced Research Projects Agency (DARPA) . This workshop brought together leaders in the software engineering research and development community to describe (1) important classes of future software-reliant systems and their associated software engineering challenges, and (2) research methods, tools, and practices that are needed to make those systems feasible. An upcoming SEI blog post will provide a synopsis of what was covered in this workshop.

Your feedback would be appreciated on the software engineering challenges and proposed research focus areas to help inform the National Agenda for Software Engineering Study. Please email [email protected] to send your thoughts and comments on the software engineering study & research roadmap or to volunteer as a potential reviewer of study drafts. Thank you.

Author Page

Digital library publications, send a message, more by the author, application of large language models (llms) in software engineering: overblown hype or disruptive change, october 2, 2023 • by ipek ozkaya , anita carleton , john e. robert , douglas schmidt (vanderbilt university), join the sei and white house ostp to explore the future of software and ai engineering, may 30, 2023 • by anita carleton , john e. robert , mark h. klein , douglas schmidt (vanderbilt university) , erin harper, software engineering as a strategic advantage: a national roadmap for the future, november 15, 2021 • by anita carleton , john e. robert , mark h. klein , erin harper, more in software engineering research and development, applying the sei sbom framework, february 5, 2024 • by carol woody, 10 benefits and 10 challenges of applying large language models to dod software acquisition, january 22, 2024 • by john e. robert , douglas schmidt (vanderbilt university), the latest work from the sei, january 15, 2024 • by douglas schmidt (vanderbilt university), the top 10 blog posts of 2023, january 8, 2024 • by douglas schmidt (vanderbilt university), applying generative ai to software engineering: navigating ethical and educational landscapes, december 11, 2023 • by john e. robert , douglas schmidt (vanderbilt university), get updates on our latest work..

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At the 2022 Research Review, our researchers detail how they are forging a new path for software engineering by executing the SEI’s technical strategy to deliver tangible results.

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Human-Centered Approaches in Modern Software Engineering

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In today's modern world, software is an integral part of our daily lives, influencing everything from business to culture and shaping our interactions with technology. However, a significant issue persists: many software development practices fail to adequately consider users' and vendors' needs, behaviors, ...

Keywords : User requirements, Design thinking, Requirements engineering, User-centered design, Human Factors in Software, Behavioral Requirements Engineering

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Software Engineer Research Paper Topics 2021: Top 5

Whether you’re studying in advance or you’re close to getting that Software Engineering degree, it’s crucial that you look for possible research paper topics in advance. This will help you have an advantage in your course.

First off, remember that software engineering revolves around tech development and improvement.

Hence, your research paper should have the same goal. It shouldn’t be too complex so that you can go through it smoothly. At the same time, it shouldn’t be too easy to the point that it can be looked up online.

Choosing can be a difficult task. Students are often choosing buy assignment from a professional writer because of the wrong topic choice. Thus, to help you land on the best topic for your needs, we have listed the top 5 software engineer research paper topics in the next sections.

Machine Learning

Machine learning is one of the most used research topics of software engineers. If you’re not yet familiar with this, it’s a field that revolves around producing programs that improve its algorithm on its own just by the use of existing data and experience.

Basically, the art of machine learning aims to make intelligent tools. Here, you will need to use various statistical methods for your computers’ algorithms. This somehow makes it a complex and long topic.

Even so, the good thing about the said field is it covers a lot of subtopics. These can include using machine learning for face spoof detection, iris detection, sentiment analysis technique, and likes. Usually, though, machine learning will go hand in hand with certain detection systems.

Artificial Intelligence

Artificial Intelligence is a much easier concept than machine learning. Note, though, that the latter is just another type of AI tool.

AI refers to the human-like intelligence integrated into machines and computer programs. Focusing on this will give you much more topics to write about. Since it’s present in a lot of fields like gaming, marketing, and even random automated tasks, you will have more materials to refer to.

Some things that you can write about in your paper include AI’s relationship with software engineering, robotics, and natural processing. You can also write about the different types of artificial intelligence tools for a more guided research paper.

Internet Of Things

Another topic that you can write about is the Internet of Things, or more commonly known as IoT . This refers to interconnected devices, machines, or even living beings as long as a network exists.

Writing about IoT will open a huge array of possibilities to write about. You can talk about whether the topic is a problem that needs additional solutions or improvements. At the same time, you will be able to talk about specific machine requirements since IoT works mainly with communication servers.

In addition, the concept of the Internet of Things is also used in several fields like agriculture, e-commerce, and medicine. Because of this, you can rest assured that you won’t run out of things to talk about or refer to.

Software Development Models

Next up, we have software development models. If you want to write about a research paper(or maybe you decided to purchase custom research paper ?) relating to how one can start building an app or software, then using software development models as a topic is a good choice.

Here, you can choose to write about what the concept is or delve deeper into its different types. You can look into the Waterfall Model, V-Model, Incremental, RAD, Agile, Iterative, Spiral, and Prototype. You can choose either one or all of the models and then relate them to software engineering.

Clone Management

One of the most important elements in software engineering is the clone base. Hence, using this as a research topic will help you stay relevant to your course and its needs. In particular, you can focus on clone management.

Clone management is a task that revolves around ensuring that a database is free from error and duplicated codes. What makes this a good topic is its materials are still limited in the field of software engineering. This is compared to other clone-related topics. Hence, you can ensure a distinct topic for your paper.

To land on the best topic, take your interest into account. Look for the field that makes you curious and entertained. In this way, you can build motivation to actually know more about it, and not just for the sake of submitting.

Another good tip is to choose a unique topic. The ones we discussed above can be considered unique since they are some of the latest software-related topics. If you’re going to use a common one, then make sure that you put your own little twist to it. You can also consider seeing the topic in a different light.

Anyhow, your research paper, its grade, and overall quality will greatly depend on what you choose to write about.

Latest Thesis and Research Topics in Software Engineering

Unique software engineering research topics for students.

more software engineers are needed as a result of the growing reliance on technology in both personal and professional spheres of life. Software engineering research topics are essential for solving complicated issues, increasing productivity, and fostering innovation. While software engineering is so important, it is equally difficult for students to get their degree in Software engineering.

Being said that many students struggle to keep up academically because software engineering is one of the most desired degrees. The final year thesis or dissertation is the most challenging assignment; many students are on the edge of losing their minds over it. While writing a thesis is one duty, coming up with an original and creative software engineering research topic is the first and most challenging step. Students with their assignments and activities don’t have enough time or energy to build a topic that is exactly right for them, finding a topic that is feasible and corresponds with your interests requires a lot of effort.

However this issue can be resolved as our PhD experts can provide you with well researched software engineering dissertation topics . We have plenty of topics for you to choose from mentioned below, and even if you don’t find anything according to your interests here you can simply contact us and request your topics according to your requirements and our experts will get you a tailored software engineering thesis topic.

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List of Free Software Engineering Research Topics

An analysis of the undertaking of good outcome factors and difficulties in software engineering projects:, how “the research guardian” can help you a lot.

Our top thesis writing experts are available 24/7 to assist you the right university projects. Whether its critical literature reviews to complete your PhD. or Master Levels thesis.

Automated software testing and quality control:

The study aims to improve programming testing and quality control through the execution of mechanized testing methods.

Objectives:

To efficiently detect software defeat and ensure complete test coverage, create an automated testing framework.
To determine which automated testing frameworks and tools are best suited to software development.
To analyze key metrics, and contrast them with the manual testing method to investigate the effects.

Impact of DevOps practices on software development:

The study aims to examine how DevOps practices affect software development productivity and efficiency.

To encourage cross-functional teams to collaborate, share information, and jointly advanced the development process.
To automate testing procedures like unit root tests, integration tests, and regression tests.
To change the activities for quality assurance and testing in the development process.

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Role of upgrading software security to enhance protection:

The aim of upgrading programming security through weakness identification and enhancing protection from possible breach

To find security flaws and weaknesses early on, employ, methods like vulnerability scanning, code reviews, and penetration testing.
To reduce the likelihood of being exploited, establish a procedure for resolving vulnerabilities as soon as possible.
To provide extensive security awareness and training programs, an organization can foster a security-conscious culture.

Adoption and effectiveness of continuous development:

The study aims to identify how effectively software engineering can be used for continuous development along with integration practices

To determine the benefit of implementing continuous deployment practices in numbers.
To evaluate the effect of computerizing the arrangement cycle, including code joining, testing, and delivery to the executive.
To analyze the impact of continuous integration practices on software development lifecycle enhancement.
To analyze how team communication and collaboration are affected by adopting software engineering practices and continuous development.

Looking For Customize Thesis Topics?

Take a review of different varieties of thesis topics and samples from our website TheResearchGuardian.com on multiple subjects for every educational level.

Planning and assess client-driven approaches in software programming:

The study aims to plan and assess client driven approaches to programing necessities and designing.

To identify the beneficial client-driven approaches necessary for programming and designing.
To ensure the successful implementation of these approaches in an organization.
To investigate the outcomes of these approaches in the success or failure of an organization.

Analyzing software metrics and their applications:

The study aims to analyze software metrics and their application to predictive software quality assurance.

To evaluate a comprehensive set of software metrics that can shed light on software product quality.
To create predictive models that make use of the software metrics that have been identified to predict potential risk and quality issues.
To compare the predictions made by the predictive models to actual software quality outcomes.

Applying Block chain Innovation:

The study aims to investigate how the distinctive characteristics of Block chain technology can be used to enhance software development and deployment process

To assess the potential use cases and advantages of coordinating block chain innovation into the product advancement lifecycle.
To investigate the application of block chain for transparent deployment histories, and decentralized package management.
To influence block chain’s straightforwardness to work with reviewing and consistence process in programming advancement.

Investigation of augmented and Virtual Reality into Software Engineering Methods and Tools:

The study aims to deeply analyse the integration of Augmented and Virtual Reality into Software Engineering Methods and tools to enhance the efficiency

To measure the impact of the integration of AR and VR technologies on software engineering
To examine the practical and technical obstacles to incorporate to incorporating augmented reality and virtual reality into existing software engineering techniques and tools.
To analyze existing frameworks and solution that make it possible to integrate AR and VR Software.

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Ten recommendations for software engineering in research

Janna hastings.

Cheminformatics and Metabolism, European Molecular Biology Laboratory – European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Hinxton, UK

Kenneth Haug

Christoph steinbeck.

Research in the context of data-driven science requires a backbone of well-written software, but scientific researchers are typically not trained at length in software engineering, the principles for creating better software products. To address this gap, in particular for young researchers new to programming, we give ten recommendations to ensure the usability, sustainability and practicality of research software.

Scientific research increasingly harnesses computing as a platform [ 1 ], and the size, complexity, diversity and relatively high availability of research datasets in a variety of formats is a strong driver to deliver well-designed, efficient and maintainable software and tools. As the frontier of science evolves, new tools constantly need to be written; however scientists, in particular early-career researchers, might not have received training in software engineering [ 2 ], thus their code is in jeopardy of being difficult and costly to maintain and re-use.

To address this gap, we have compiled ten brief software engineering recommendations.

Recommendations

Keep it simple.

Every software project starts somewhere. A rule of thumb is to start as simply as you possibly can . Significantly more problems are created by over-engineering than under-engineering. Simplicity starts with design: a clean and elegant data model is a kind of simplicity that leads naturally to efficient algorithms.

Do the simplest thing that could possibly work, and then double-check it really does work.

Test, test, test

For objectivity, large software development efforts assign different people to test software than those who develop it. This is a luxury not available in most research labs, but there are robust testing strategies available to even the smallest project.

Unit tests are software tests which are executed automatically on a regular basis. In test driven development, the tests are written first, serving as a specification and checking every aspect of the intended functionality as it is developed [ 3 ]. One must make sure that unit tests exhaustively simulate all possible – not only that which seems reasonable – inputs to each method.

Do not repeat yourself

Do not be tempted to use the copy-paste-modify coding technique when you encounter similar requirements. Even though this seems to be the simplest approach, it will not remain simple, because important lines of code will end up duplicated. When making changes, you will have to do them twice, taking twice as long, and you may forget an obscure place to which you copied that code, leaving a bug.

Automated tools, such as Simian [ 4 ], can help to detect and fix duplication in existing codebases. To fix duplications or bugs, consider writing a library with methods that can be called when needed.

Use a modular design

Modules act as building blocks that can be glued together to achieve overall system functionality. They hide the details of their implementation behind a public interface, which provides all the methods that should be used. Users should code – and test – to the interface rather than the implementation [ 5 ]. Thus, concrete implementation details can change without impacting downstream users of the module. Application programming interfaces (APIs) can be shared between different implementation providers.

Scrutinise modules and libraries that already exist for the functionality you need. Do not rewrite what you can profitably re-use – and do not be put off if the best candidate third-party library contains more functionality than you need (now).

Involve your users

Users know what they need software to do. Let them try the software as early as possible, and make it easy for them to give feedback, via a mailing list or an issue tracker. In an open source software development paradigm, your users can become co-developers. In closed-source and commercial paradigms, you can offer early-access beta releases to a trusted group.

Many sophisticated methods have been developed for user experience analysis. For example, you could hold an interactive workshop [ 6 ].

Resist gold plating

Sometimes, users ask for too much, leading to feature creep or “gold plating”. Learn to tell the difference between essential features and the long list of wishes users may have. Prioritise aggressively with as broad a collection of stakeholders as possible, perhaps using “game-storming” techniques [ 7 ].

Gold plating is a challenge in all phases of development, not only in the early stages of requirements analysis. In its most mischievous disguise, just a little something is added in every iterative project meeting. Those little somethings add up.

Document everything

Comprehensive documentation helps other developers who may take over your code, and will also help you in the future. Use code comments for in-line documentation, especially for any technically challenging blocks, and public interface methods. However, there is no need for comments that mirror the exact detail of code line-by-line.

It is better to have two or three lines of code that are easy to understand than to have one incomprehensible line, for example see Figure Figure1 1 .

An external file that holds a picture, illustration, etc.
Object name is 13742_2014_62_Fig1_HTML.jpg

An example of incomprehensible code: What does this code actually do? It contains a bug; is it easy to spot?

Write clean code [ 8 ] that you would want to maintain long-term (Figure (Figure2). 2 ). Meaningful, readable variable and method names are a form of documentation.

An external file that holds a picture, illustration, etc.
Object name is 13742_2014_62_Fig2_HTML.jpg

This code peforms the same function, but is written more clearly.

Write an easily accessible module guide for each module, explaining the higher level view: what is the purpose of this module? How does it fit together with other modules? How does one get started using it?

Avoid spaghetti

Since GOTO-like commands fell justifiably out of favour several decades ago [ 9 ], you might believe that spaghetti code is a thing of the past. However, a similar phenomenon may be observed in inter-method and inter-module relationships (see Figures Figures3 3 and and4). 4 ). Debugging – stepping through your code as it executes line by line – can help you diagnose modern-day spaghetti code. Beware of module designs where for every unit of functionality you have to step through several different modules to discover where the error is, and along the way you have long lost the record of what the original method was actually doing or what the erroneous input was. The use of effective and granular logging is another way to trace and diagnose problems with the flow through code modules.

An external file that holds a picture, illustration, etc.
Object name is 13742_2014_62_Fig3_HTML.jpg

An unhealthy module design for ‘biotool‘ with multiple interdependencies between different packages. An addition of functionality to the system (such as supporting a new field) requires updating the software in many different places. Refactoring into a simpler architecture would improve maintainability.

An external file that holds a picture, illustration, etc.
Object name is 13742_2014_62_Fig4_HTML.jpg

The functional units from the biotool architecture can be grouped together in a refactoring process, putting similar functions together. The result may resemble a Model-View-Controller architecture.

Optimise last

Beware of optimising too early. Although research applications are often performance-critical, until you truly encounter the wide range of inputs that your software will eventually run against in the production environment, it may not be possible to anticipate where the real bottlenecks will lie. Develop the correct functionality first, deploy it and then continuously improve it using repeated evaluation of the system running time as a guide (while your unit tests keep checking that the system is doing what it should).

Evolution, not revolution

Maintenance becomes harder as a system gets older. Take time on a regular basis to revisit the codebase, and consider whether it can be renovated and improved [ 10 ]. However, the urge to rewrite an entire system from the beginning should be avoided, unless it is really the only option or the system is very small. Be pragmatic [ 11 ] – you may never finish the rewrite [ 12 ]. This is especially true for systems that were written without following the preceding recommendations.

Use a good version control system (e.g., Git [ 13 ]) and a central repository (e.g., GitHub [ 14 ]). In general, commit early and commit often, and not only when refactoring.

Effective software engineering is a challenge in any enterprise, but may be even more so in the research context. Among other reasons, the research context can encourage a rapid turnover of staff, with the result that knowledge about legacy systems is lost. There can be a shortage of software engineering-specific training, and the “publish or perish” culture may incentivise taking shortcuts.

The recommendations above give a brief introduction to established best practices in software engineering that may serve as a useful reference. Some of these recommendations may be debated in some contexts, but nevertheless are important to understand and master. To learn more, Table Table1 1 lists some additional online and educational resources.

Acknowledgements

This commentary is based on a presentation given by JH at a workshop on Software Engineering held at the 2014 annual Metabolomics conference in Tsuruoka, Japan. The authors would like to thank Saravanan Dayalan for organising the workshop and giving JH the opportunity to present. We would furthermore like to thank Robert P. Davey and Chris Mungall for their careful and helpful reviews of an earlier version of this manuscript.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

JH prepared the initial draft. All authors contributed to, and have read and approved, the final version.

Contributor Information

Janna Hastings, Email: ku.ca.ibe@sgnitsah .

Kenneth Haug, Email: ku.ca.ibe@htennek .

Christoph Steinbeck, Email: ku.ca.ibe@kcebniets .

When Software Engineering Meets Quantum Computing

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Introduction

The Impact of Quantum Computing

Why quantum software engineering, classical vs. quantum software engineering.

binary code in detail of quantum computer illustration

Over the last few decades, quantum computing (QC) has intrigued scientists, engineers, and the public across the globe. Quantum computers use quantum superposition to perform many computations, in parallel, that are not possible with classical computers, resulting in tremendous computational power. 7 By exploiting such power, QC and quantum software enable many applications that are typically out of the reach of classical computing, such as drug discovery and faster artificial intelligence (AI) techniques.

Quantum computers are currently being developed with a variety of technologies, such as superconducting and ion trapping. Private companies, such as Google and IBM, are building their own quantum computers, while public entities are investing in quantum technologies. For example, the European Union Commission is spending €1 billion on quantum technologies (“EU’s Quantum Flagship Project’s Website” a ). Currently, the key goal for quantum computers is to reduce hardware errors that limit their practical uses. Regardless of the eventual technology that wins the quantum hardware race, the key enabler for building QC applications is quantum software (see Figure 1 ).

Quantum software needs to be supported with a quantum software stack, ranging from operating systems to compilers and programming languages, (see examples in Table 1 ) as postulated by Bertels et al. from the University of Porto. 3 Quantum software engineering ( QSE ) enables the cost-effective and scalable development of dependable quantum software to build revolutionary quantum software applications in many domains—for example, finance, chemistry, healthcare, and agriculture (see Figure 1 and Table 1 ). However, effective quantum software applications cannot be developed with classical software engineering methods due to quantum computing’s inherent characteristics—for instance, superposition and entanglement. Thus, we need to build novel QSE methodologies (with tool support) that cover different phases of QSE, possibly including requirements engineering, modeling, coding, testing, and debugging as shown in Figure 1 .

In this article, we first present a general view of quantum computing’s potential impact, followed by some highlights of EU-level QC initiatives. We then argue the need for QSE, present the state of the art of QSE from multiple aspects (testing, for example) by comparing quantum computers with their classical counterparts, and shed light on possible research directions.

Quantum computing is primed to solve a broad spectrum of computationally expensive societal and industrial problems. Notable examples include accelerated drug discovery and vaccine development in healthcare, portfolio management and optimization in finance, and complex simulations in physics to better understand our universe. As a result, QC’s success will inevitably and significantly impact our day-to-day lives and revolutionize most industries across many domains. Such impact must be realized via quantum software, the development of which should be systematically powered by QSE. Scientifically speaking, QSE will open new areas of research to develop real applications by fostering research communities across disciplines (such as computer science, software engineering, mathematics, and physics) and interactions with other fields such as medicine, chemistry, and finance. Table 1 summarizes various dimensions of QC with examples.

EU-level quantum initiatives. Efforts to build quantum computers in Europe are increasing. VTT–Technical Research Centre of Finland, together with IQM, aims to build Finland’s first 25-qubit, fully functional quantum computer by 2024. In Sweden, the Wallenberg Centre for Quantum Technology at Chalmers is building a superconducting quantum computer capable of up to 100 qubits. The Future and Emerging Technologies’ Quantum Technologies Flagship program also funds projects to build quantum computers. For example, AQTION is building Europe’s first ion-trapped quantum computer, while OpenSuperQ is focused on building a 100-qubit superconducting QC. To boost research on the development of novel QC applications in Germany, Fraunhofer installed an IBM Quantum System One to provide access to organizations interested in developing QC applications. Finally, NordiQuEst is a new collaborative effort between four Nordic countries and Estonia to build a dedicated Nordic-Estonian QC ecosystem that will integrate various quantum computers and emulators and make them accessible to the Nordic-Estonian region to accelerate QC research, development, and education.

Building practical and real-life QC applications requires the implementation of quantum algorithms as software. Learning from the classical computing realm, developing dependable software entails following a software development life cycle ( SDLC ), which typically includes requirements engineering, architecture and design, development, testing, debugging, and maintenance phases.

Given that quantum software development is relatively new, an SDLC for quantum software doesn’t exist. However, quantum programming languages are available to implement quantum algorithms (see examples in Table 1 ). In their current state, these languages allow programming at the lower level—for instance, as quantum circuits consisting of quantum gates. Figure 2 shows a quantum program example in IBM’s Qiskit performing quantum entanglement, its equivalent quantum circuit in the middle, and execution result on the right side.

Programming quantum circuits is challenging, as evidenced in the example, because it requires a specialized background in quantum physics, including an understanding of how quantum gates work. Unfortunately, classical computing programmers do not often possess such a background, thus making it difficult for them to program quantum computers. Moreover, in the context of quantum SDLC, quantum programming is just one aspect; attention must be given to other SDLC phases, such as requirements, design, and architecture; verification and validation; and maintenance.

Quantum software requirements engineering and quantum software modeling. Due to the increasing complexity of software application domains, requirements engineering is critical, as it is the process of eliciting, specifying/modeling, managing requirements, among others. During the process, various stakeholders—domain experts and software developers, for example—interact, and the resulting requirements serve as key artifacts to drive software design and development. From this perspective, we consider that requirements engineering in the quantum world aligns with requirements engineering of its classical computing counterpart (see Table 2 for details). However, QC brings new challenges.

First, its software engineers often find its application domains—for instance, radiotherapy optimization or drug discovery—hard to comprehend. Second, quantum software engineers must also equip themselves with basic knowledge about quantum mechanics, linear algebra, algorithms and their analysis, and more. Therefore, requirements engineering is very important for easing communication among various stakeholders while raising the level of abstraction in understanding the domain and linking the domain to analysis, design, and implementation. To the best of our knowledge, requirements engineering for quantum software is an uncharted area of research. There has not been any publication in this area yet. We argue that, as with classical software, quantum software engineering requires the development of novel elicitation, specification, modeling, analysis, and verification methods.

Quantum finite-state machines, and the study of their formal properties, have been investigated in the literature. 8 However, their application to quantum software modeling remains unstudied. Recently, there has been an increasing interest in extending the Unified Modeling Language (UML) to model quantum software, mainly in the classical software engineering community as highlighted by European researchers. 2 More research is needed, though, to determine whether extending UML is sufficient or more domain-specific modeling solutions are required. In general, there are many opportunities for quantum software modeling, such as developing novel and intuitive quantum modeling notations and methodologies, verification and validation with quantum software models, and empowering code/circuit generation.

Quantum software testing. It is important to ensure quantum programs are correct—that is, they can deliver their intended functionalities. Testing quantum programs is difficult compared to classical software due to their inherent characteristics, including their probabilistic nature; computations in superpositions; the use of advanced features, such as entanglement; a difficulty in reading or estimating quantum program states in superposition; and a lack of precise test oracles. Thus, there is a need for novel, automated, and systematic methods for testing quantum programs. Quantum software testing is garnering increased attention, and several papers have recently been published, with significant contributions from European researchers. 1 , 6 , 9 , 10

Several research areas need to be explored, such as how to define and check (with relevant statistics, for instance) quantum test oracles without destroying superposition, and how to cost-effectively find test data that can break a quantum program. Given hardware noises in quantum computers, testing techniques must also be noise-aware. In general, we foresee the need to build theoretical foundations of quantum software testing, including coverage criteria, test models, and test strategies. Test strategies consist of test oracles, test data, and test cases, and can be designed by considering fault types, metamorphic testing to deal with test oracle issues, and mutation analysis. To maximize the benefit, all test techniques are expected to be independent of a quantum programming language. Furthermore, we need practical applications, extensive empirical evaluations of testing techniques, and the creation of benchmarks for the community. Several automated quantum software testing tools have recently been developed, with major contributions by European researchers such as Quito, Muskit, QuSBT, QsharpCheck, and QuCAT.

Quantum software debugging. Observed failures in quantum pro-grams—for instance, found with testing—need to be diagnosed with the debugging process to isolate and patch the code to fix the failure. This process typically comprises multiple tactics usually found in debuggers, such as relying on print statements in code to achieve interactive debugging. Similarly, we need quantum software debugging tactics, implemented in debuggers, to cost-effectively diagnose and resolve quantum software failures. However, the development of effective debugging techniques faces several challenges as discussed in a key debugging work: 4 an inability to directly monitor quantum software states in superposition; the understanding of quantum software states, when possible (for instance, in quantum computer simulators), can be unintuitive; and a lack of best practices, in general, to perform debugging.

Several research opportunities exist for debugging quantum programs: tailoring classical debugging tactics (backtracking and cause elimination, for example) to debug programs on quantum simulators and developing novel tactics to debug on real quantum computers; novel visualization approaches to inspect values without the need to measure quantum states, with intuitive visualizations comprehensible by humans; and novel ways to infer quantum software states using statistical 4 and projection-based assertions (for example, see Li et al. 5 ), in addition to developing novel assertion types.

Quantum computing is on the rise and will, no doubt, revolutionize many technologies. It will transform our understanding of and the way we deal with complex problems and challenges. Quantum software engineering is key to the systematic and cost-effective creation of tomorrow’s powerful, reliable, and practical QC applications.

Compared with classical computing, QC’s inherent complexity and its complex application domains—drug discovery, for example—present new multidimensional challenges that emphasize the significance of QSE. Fascinated by this observation, we presented in this article the key highlights of QC activities in Europe, key QSE innovations (when compared with classical software engineering), and open QSE research directions. This is the time to embrace QC and form the QSE community in Europe and globally.

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Research Topics in Software Engineering

This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research.

Each student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis. Active participation is required (a presentation of a paper as well as participation in discussions).

The aim of this seminar is to introduce students to recent research results in the area of programming languages and software engineering. To accomplish that, students will study and present research papers in the area as well as participate in paper discussions. The papers will span topics in both theory and practice, including papers on program verification, program analysis, testing, programming language design, and development tools.

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Breakdown of Topics for the Software Engineering Models and Methods KA
150+ Best Engineering Research Topics for Students To Consider
(PDF) Writing good software engineering research papers
Research in Software Engineering Paradigms and Methods
Top 10 software engineering and computer science topics
150+ Best Research Paper Topics For Software Engineering

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COMMENTS

Top 10 Software Engineer Research Topics for 2024
Top Software Engineer Research Topics. 1. Artificial Intelligence and Software Engineering. Intersections between AI and SE. The creation of AI-powered software engineering tools is one potential research area at the intersection of artificial intelligence (AI) and software engineering. These technologies use AI techniques that include machine ...
Software Engineering's Top Topics, Trends, and Researchers
For this theme issue on the 50th anniversary of software engineering (SE), Redirections offers an overview of the twists, turns, and numerous redirections seen over the years in the SE research literature. Nearly a dozen topics have dominated the past few decades of SE research—and these have been redirected many times. Some are gaining popularity, whereas others are becoming increasingly ...
software engineering Latest Research Papers
End To End . Predictive Software. The paper examines the principles of the Predictive Software Engineering (PSE) framework. The authors examine how PSE enables custom software development companies to offer transparent services and products while staying within the intended budget and a guaranteed budget.
Journal of Software Engineering Research and Development
They wanted to define values and basic principles for better software development. On top of being brought into focus, the ... Philipp Hohl, Jil Klünder, Arie van Bennekum, Ryan Lockard, James Gifford, Jürgen Münch, Michael Stupperich and Kurt Schneider. Journal of Software Engineering Research and Development 2018 6 :15.
Trending Topics in Software Engineering
In this new column Trending Topics in Software Engineering, we aim at providing insights, reports, and outlooks on how researchers and practitioners around the world are working (or planning to work) on those trends. We intend to collect the challenges they are facing or foresee, and explore them in future issues.
150 Best Research Paper Topics For Software Engineering
This paper reviews software tools to solve complicated tasks in the analysis of data. The paper compares NVivo, HyperRESEARCH, and Dedoose. Data Scientist and Software Development. Data scientists convert data into insights, giving elaborate guidance to those who use the data to make educated decisions and take action.
Software Engineering
Software Engineering. At Google, we pride ourselves on our ability to develop and launch new products and features at a very fast pace. This is made possible in part by our world-class engineers, but our approach to software development enables us to balance speed and quality, and is integral to our success. Our obsession for speed and scale is ...
Architecting the Future of Software Engineering: A Research and
In close collaboration with our advisory board and other leaders in the software engineering community, we have developed a research roadmap with six focus areas. Figure 1 shows those areas and outlines a suggested course of research topics to undertake. Short descriptions of each focus area and its challenges follow.
2022 Research Review
2022 Research Review. At the 2022 Research Review, our researchers detail how they are forging a new path for software engineering by executing the SEI's technical strategy to deliver tangible results. Researchers highlight methods, prototypes, and tools aimed at the most important problems facing the DoD, industry, and academia, including AI ...
Software Engineering and Intelligent Systems
Software engineering and intelligent systems are two dynamic and interrelated fields that have witnessed significant advancements and transformations in recent years. The convergence of these domains has led to the development of innovative applications and solutions that are shaping various industries, from healthcare and finance to transportation and manufacturing.This Research Topic aims to ...
Advances in Software Science and Engineering
Software engineering is a discipline that adopts engineering approaches to develop large-scale software towards high productivity, low cost, trustworthy quality, and controllable development schedule [1]. ... and tools for supporting industrial practices and processes. Potential topics of contributions to this Research Topic include but are not ...
Human-Centered Approaches in Modern Software Engineering
This is the central focus of our issue endeavor, where we aim to explore the convergence of social sciences, design principles, and software engineering to establish a more human-centered paradigm. This Research Topic highlights techniques and concepts that can infuse empathy and fairness into software development.
PDF A National Agenda for Software Engineering Research & Development
5.6.5 Research Topics 60 5.7 Engineering AI-Enabled Software Systems Research Focus Area 61 5.7.1 Goals 61 5.7.2 Limitations of Current Practice 62 ... with the software engineering research communities, to working with our distributed team to assemble the study, all of it had to be done in a virtual setting. I want to thank everyone for their ...
Research in Software Engineering (RiSE)
Our mission is to make everyone a programmer and maximize the productivity of every programmer. This will democratize computing to empower every person and every organization to achieve more. We achieve our vision through open-ended fundamental research in programming languages, software engineering, and automated reasoning.
Software Engineer Research Paper Topics 2021: Top 5
Students are often choosing buy assignment from a professional writer because of the wrong topic choice. Thus, to help you land on the best topic for your needs, we have listed the top 5 software engineer research paper topics in the next sections. Machine Learning. Machine learning is one of the most used research topics of software engineers.
Unique List of Software Engineering Research Topics
Unique Software Engineering Research Topics for Students. more software engineers are needed as a result of the growing reliance on technology in both personal and professional spheres of life. Software engineering research topics are essential for solving complicated issues, increasing productivity, and fostering innovation.
Software Engineering
Abstract. Software engineering is a pragmatic discipline. From the very beginning, the mindset of the software engineering research community has been focused on solving problems faced by practicing software engineers [1], and hence, much of software engineering work is motivated by pragmatic outcomes.
What are the latest research topics in software engineering
There are many hot research topics in software engineering. For example, you may look at the following two topics: These are some hot research topic related to software engineering like ...
Research index
Topics. Adversarial examples (4) Audio generation (2) Community (12) Compute (8) ... Software engineering (21) Sparsity (2) Speech recognition (1) Summarization (4) ... Research Papers. Feb 15, 2024 February 15, 2024. Video generation models as world simulators.
Research Topics in Software Engineering
Overview. This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research. Each student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis.
Ten recommendations for software engineering in research
Research in the context of data-driven science requires a backbone of well-written software, but scientific researchers are typically not trained at length in software engineering, the principles for creating better software products. To address this gap, in particular for young researchers new to programming, we give ten recommendations to ...
(PDF) Software Engineering Research Topics
The software engineering research on CE is still in its infancy. There are future research opportunities in evaluation research of technical topics and investigations of ethical experimentation.
When Software Engineering Meets Quantum Computing
An overview of quantum software engineering. Quantum software needs to be supported with a quantum software stack, ranging from operating systems to compilers and programming languages, (see examples in Table 1) as postulated by Bertels et al. from the University of Porto. 3 Quantum software engineering (QSE) enables the cost-effective and ...
Research Topics in Software Engineering
Overview. This seminar is an opportunity to become familiar with current research in software engineering and more generally with the methods and challenges of scientific research. Each student will be asked to study some papers from the recent software engineering literature and review them. This is an exercise in critical review and analysis.

Top 10 Software Engineer Research Topics for 2024