computer science thesis structure

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Thesis Examples

Latex Example (shortened M.Sc. with urthesis.sty)  (ZIP)

Latex Example (complete M.Sc. with no .sty)  (ZIP)

How to Write a M.Sc. Thesis

The following guide to writing an M.Sc. thesis was prepared by Howard Hamilton and Brien Maguire, based on previous guides by Alan Mackworth (University of British Columbia) and Nick Cercone (Simon Fraser University), with their permission.

Quick Guide to the M.Sc. Thesis

An acceptable M.Sc. thesis in Computer Science should attempt to satisfy one or more of the following criteria:

• Original research results are explained clearly and concisely.
• The thesis explains a novel exploratory implementation or a novel empirical study whose results will be of interest to the Computer Science community in general and to a portion of the Computer Science community in particular, e.g., Artificial Intelligence, Computational Complexity, etc.
• Novel implementation techniques are outlined, generalized, and explained.
• Theoretical results are obtained, explained, proven, and (worst, best, average) case analysis is performed where applicable.
• The implementation of a practical piece of nontrivial software whose availability could have some impact on the Computer Science community. Examples are a distributed file system for a mobile computing environment and a program featuring the application of artificial intelligence knowledge representation and planning techniques to intelligent computer assisted learning software.

Writing an acceptable thesis can be a painful and arduous task, especially if you have not written much before. A good methodology to follow, immediately upon completion of the required courses, is to keep a paper or electronic research notebook and commit to writing research oriented notes in it every day. From time to time, organize or reorganize your notes under headings that capture important categories of your thoughts. This journal of your research activities can serve as a very rough draft of your thesis by the time you complete your research. From these notes to a first M.Sc. thesis draft is a much less painful experience than to start a draft from scratch many months after your initial investigations. To help structure an M.Sc. thesis, the following guide may help.

One Formula for an M.Sc. Thesis for Computer Science

Chapter 1 Introduction: This chapter contains a discussion of the general area of research which you plan to explore in the thesis. It should contain a summary of the work you propose to carry out and the motivations you can cite for performing this work. Describe the general problem that you are working towards solving and the specific problem that you attempt to solve in the thesis. For example, the general problem may be finding an algorithm to help an artificial agent discover a path in a novel environment, and the specific problem may be evaluating the relative effectiveness and efficiency of five particular named approaches to finding the shortest path in a graph where each node is connected to at most four neighbours, with no knowledge of the graph except that obtained by exploration. This chapter should also explain the motivations for solving each of the general problem and your specific problem. The chapter should end with a guide to the reader on the composition and contents of the rest of the thesis, chapter by chapter. If there are various paths through the thesis, these should also be explained in Chapter 1.

Chapter 2 Limited Overview of the Field: This chapter contains a specialized overview of that part of a particular field in which you are doing M.Sc. thesis research, for example, paramodulation techniques for automated theorem proving or bubble figure modelling strategies for animation systems. The survey should not be an exhaustive survey but rather should impose some structure on your field of research endeavour and carve out your niche within the structure you impose. You should make generous use of illustrative examples and citations to current research.

Chapter 3 My Theory/Solution/Algorithm/Program: This chapter outlines your proposed solution to the specific problem described in Chapter 1. The solution may be an extension to, an improvement of, or even a disproof of someone else's theory / solution / method / ...).

Chapter 4 Description of Implementation or Formalism: This chapter describes your implementation or formalism. Depending on its length, it may be combined with Chapter 3. Not every thesis requires an implementation. Prototypical implementations are common and quite often acceptable although the guiding criterion is that the research problem must be clearer when you've completed your task than it was when you started!

Chapter 5 Results and Evaluation: This chapter should present the results of your thesis. You should choose criteria by which to judge your results, for example, the adequacy, coverage, efficiency, productiveness, effectiveness, elegance, user friendliness, etc., and then clearly, honestly and fairly adjudicate your results according to fair measures and report those results. You should repeat, whenever possible, these tests against competing or previous approaches (if you are clever you will win hands down in such comparisons or such comparisons will be obviated by system differences). The competing or previous approaches you compare against must have been introduced in Chapter 2 (in fact that may be the only reason they actively appear in Chapter 2) and you should include pointers back to Chapter 2. Be honest in your evaluations. If you give other approaches the benefit of the doubt every time, and develop a superior technique, your results will be all the more impressive.

Chapter 6 Conclusions: This chapter should summarize the achievements of your thesis and discuss their impact on the research questions you raised in Chapter 1. Use the distinctive phrasing "An original contribution of this thesis is" to identify your original contributions to research. If you solved the specific problem described in Chapter 1, you should explicitly say so here. If you did not, you should also make this clear. You should indicate open issues and directions for further or future work in this area with your estimates of relevance to the field, importance and amount of work required.

References Complete references for all cited works. This should not be a bibliography of everything you have read in your area.

Appendices include technical material (program listings, output, graphical plots of data, detailed tables of experimental results, detailed proofs, etc.) which would disrupt the flow of the thesis but should be made available to help explain or provide details to the curious reader.

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Books to Help Organize Your Writing

• Thesis Help Books In Kemp Library
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• Research Help Books In Kemp Library
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• Useful Articles

• Graduate Writing Across the Disciplines, Introduction by Marilee Brooks-Gillies, Elena G. Garcia, Soo Hyon Kim, Katie Manthey and Trixie Smith
• Peer Portal: Quality Enhancement in Thesis Writing Using Self-Managed Peer Review on a Mass Scale by Naghmeg Aghaee and Henrik Hansson

So you have to write a thesis...

• Useful Websites

The number one rule for writing your thesis is  be organized .  This may be different for everyone, but here is the basic structure (see red slides below) on what your masters thesis or dissertation should include. Also included are videos, books, writing tips, websites, and articles that may assist you.  

Your specific discipline may have specific requirements for you to follow. Please consult with your thesis advisor whenever you have questions.

If you are having trouble with research please do not hesitate to reach out to a librarian (see the Stuck? page for contact information).

This video was created by Lund University in Sweden and is a great resource.  Please keep in mind that they use slightly different words for their sections such as "summary" instead of "conclusion", but the content that should be included is the same and the way they explain it is succinct and accurate. 

This video by Massey University (New Zealand) is a recorded lecture on how to write a thesis with several examples and good advice throughout. Please keep in mind that here too, some of the vocabulary is different but the content is useful. 

• Basic Thesis Guide by Dr. Kendra Gaines, University of Arizona
• Guidelines for Writing a Thesis or Dissertaion
• If you're in the humanities this would be the heart of your research. For example if you were comparing Game of Thrones  to Shakespeare, instead of beginning with an introduction, you would jump into where you are comparing them. 
• Instead of sitting in front of your computer every day for 2 hours with writer's block, try to write daily with well defined writing goals - I'm going to write 2 pages, or create a table, etc. 
• If you miss a day, do not try to make up for it the next day. Just keep going and don't burn yourself out. Keep yourself to reasonable, realistic goals and make sure to keep a work-life balance.
• Don't worry about perfect grammar when you're doing your first draft(s).  That's easy to edit, generating new content with perfect style? Not as easy. 
• Try to keep some kind of memo pad with you at all times - on your phone, on paper, however works for you for those flashes of brilliance when you're not near your document.
• Make sure you communicate with your supervisor - do not be afraid to reach out!  Make sure you're on the right track.
• If you're research based make sure you have a clearly defined question your thesis will answer, including milestones. 
• Make and outline, including bullet points for your data/arguments in each section. This may change over time but it will help you keep track of what data needs to be collected and what information needs to be included in each chapters .
• Include all your results, not just the results that support your hypothesis - this is called cherry picking.  Be transparent. 
• Read and look at other theses in your field - this can help inspire you and answer questions as you go along. You can do this in the library, or online by visiting our dissertation databases . You can also check out Google Scholar to see what's available there. 
• How to Write a Thesis Without Losing Your Mind - Risto Sarvas

Thesis Structure

Overview of General Thesis Structure

What's in the body of my thesis?

Writethatphd.

I highly recommend the resources from @WriteThatPhD - there's great advice and frameworks shared here.

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• Last Updated: Feb 15, 2024 1:35 PM
• URL: https://esu.libguides.com/compsci

Writing Your Thesis

At this page, we provide some information necessary while writing a thesis. Basically, the same rules can be applied for any other scientific paperwork. We must admit that this information collected here is neither complete nor represents it a general rule set. Nevertheless, we try to keep it up-to-date and comprehensive. If you have comments or suggestions, please drop me a short note.

Presentation Templates

• The FAU provide templates for your presentations here

LaTeX Template

• We provide a template for your thesis: Download (new 27. July 2022) .
• Please try to stick with this layout.

General Rules and Hints

• How to write an abstract
• Motivation (Why do we care?)
• Problem statement (What problem are we trying to solve?)
• Approach (How did we go about it)
• Results (What’s the answer?)
• Conclusion (What are the implications of the answer?)
• Context: make sure to link where your work fits in
• Problem: gap in knowledge, too expensive, too slow, a deficiency, superseded technology
• Strategy: the way you will address the problem
• comment on employed hardware and software
• describe methods and techniques that build the basis of your work
• review related work(!)
• start with a theoretical approach
• describe the developed system/algorithm/method from a high-level point of view
• go ahead in presenting your developments in more detail
• whatever you have done, you must comment it, compare it to other systems, evaluate it
• usually, adequate graphs help to show the benefits of your approach
• caution: each result/graph must be discussed! what’s the reason for this peak or why have you ovserved this effect
• summarize again what your paper did, but now emphasize more the results, and comparisons
• write conclusions that can be drawn from the results found and the discussion presented in the paper
• future work (be very brief, explain what, but not much how)
• all papers and articles used in the thesis must be cited (and each reference must be used in the thesis!)
• a rough number is 20 references for a bachelor thesis and 30-40 for a master’s thesis
• avoid to cite web sites
• We highly recommend to use Endnote or BibTeX for creating the references and citings
• Further information: IEEE Rules , BibTeX
• Avoid passive voice, active voice is easier to read. There is nothing wrong saying I (or we) did it
• Avoid negative sentences: write in a positive (affirmative) voice, they are easier to understand.
• Always use vector graphics for figures (PDF, EPS, …)
• Did I spell out the main points of the interpretation of results?
• Are all equations, figures, tables numbered?
• Do all graphs, tables, diagrams have descriptive captions?
• Are all axes and scale carefully chosen to show the relevant effects?
• Are all axes labelled? Do the labals include the measurement units?
• Are citations in the caption (if a graph is borrowed)?

Further reading

• Some Advice on Writing a Technical Report
• Ein sehr schöner Überblicksartikel von Henning Schulzrinne zum Aufbau eines Papers.
• Die Webseite des Computer Science Research Methods and Writing Workshop der Iowa State University Sehr schöne Sammlung von Links zum Thema Forschen, Lesen, Schreiben
• Advice on Research and Writing
• Computer Science Student Resource Site

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The Dissertation

• Continuing to Part III

The dissertation should be written for a technically competent reader who is not necessarily familiar with the particular aspects of Computer Science involved. Better grades will arise from clarity and ease of reading, good pictures, clear explanation, minimal jargon and appropriate use of equations. Writing a dissertation requires planning and time. You should allow at least four weeks for the task.

Dissertation PDF files must be

• formatted for A4 paper;
• Typeset in 12-point font with a minimum of 2 cm margins;
• less than 15 megabytes in size;
• (ideally) use embedded fonts.

The main body of the dissertation, running from the first page of the introduction until the last page of the conclusions, shall not exceed 40 pages nor exceed 12,000 words in length (including tables and footnotes). Students should ensure the main body of their dissertation (page 3 onwards) as well as any appendices do not contain direct personal identifiers (i.e. their name or their CRSID).

Examiners and Assessors are permitted to judge your work only through study of your dissertation, although they will require your original source code to be available for them to refer to in cases where clarification is needed.

To facilitate the assessment process, the Examiners require the top-level structure of the dissertation to be strictly as follows:

Declaration of originality

Table of contents.

• Chapter 1: Introduction
• Chapter 2: Preparation
• Chapter 3: Implementation
• Chapter 4: Evaluation
• Chapter 5: Conclusions

Bibliography

Project proposal.

It is not the intention of the Examiners to constrain writers too greatly. Although the layout of the Cover Sheet and the arrangement of the Proforma are tightly specified, the organisation and length of each of the five chapters are allowed to vary considerably from one dissertation to another. Further details are given below.

The cover page

The single cover page contains

• Your Name, in the extreme top right-hand corner . 
• The Title of your Dissertation.
• The Examination for which you are a candidate.
• Your College and the Year in which you are submitting the Dissertation.

Your project title must be the same as the title approved by your Project Checkers on your project proposal.  If you want to change the title you should first discuss this with your supervisor.  If your supervisor is in agreement you will need to request a change by contacting the Teaching Administration Manager with a brief explanation for the reasons behind the change ([email protected]).  This will be approved by the Teaching Administration Manager and Chair of Examiners.

All dissertations must include an anti-plagiarism declaration immediately before the Proforma. The declaration must have exactly the following syntax:

I, [Name] of [College], being a candidate for Part II of the Computer Science Tripos, hereby declare that this dissertation and the work described in it are my own work, unaided except as may be specified below, and that the dissertation does not contain material that has already been used to any substantial extent for a comparable purpose. [In preparation of this dissertation I did not use text from AI-assisted platforms generating natural language answers to user queries, including but not limited to ChatGPT. / The project required the use of AI-assisted platform [name] in section [number], and such use is acknowledged in the text.] (use either of these sentences as appropriate) [I am content for my dissertation to be made available to the students and staff of the University.]

Signed [signature]

Date [date]

Further guidance relating to the use of AI-assisted tools can be found on the exams guidance web page .

You may either include a scanned copy of your signature or type your full name in place of a handwritten signature.

The University drafted the wording, which is similar to that relating to dissertations in a wide range of subjects; thus the "unaided except as may be specified below" clause merits some explanation:

• The clause does not require acknowledgement of the project supervision or informal conversations with peers.
• The clause is also intended to cover collaborative projects which are not now permitted in Computer Science. As such this aspect is irrelevant to Computer Science dissertations.
• This clause aside, and notwithstanding 1 and 2, candidates are required to draw attention, in the Implementation chapter, to the parts of the work which are not their own, in accordance with the Implementation section below. Other acknowledgements should be given wherever appropriate.

The Department would like past dissertations to be made available for teaching purposes and for your references. These will be accessed on the Computer Science departmental website under Raven password protection. You should include the last sentence of the declaration if you are willing for your dissertation to be accessed for these purposes; otherwise you may remove it.  Note: If in the future you would like your dissertation removed from the departmental website, you can request this by contacting the Student Admin office at [email protected].

The proforma page

The single proforma page is a preface that immediately follows the declaration of originality. The proforma page, as well as all subsequent pages of the dissertation should not include direct personal identifiers such as your name or CRSID. The Proforma must be arranged thus:

• Your candidate number.
• The Title of your Project.
• The Examination and Year.
• Word-count for the dissertation.
• Code line count: Number of lines of code written by the student in the final version of their software.
• Project Originator (if this is the student please state 'The candidate').
• Project Supervisor.
• At most 100 words describing the original aims of the project.
• At most 100 words summarising the work completed.
• At most 100 words describing any special difficulties that you faced. (In most cases the special difficulties entry will say "None".)

It is quite in order for the Proforma to point out how ambitious the original aims were and how the work completed represents the triumphant consequence of considerable effort against a background of unpredictable disasters. The substantiation of these claims will follow in the rest of the dissertation.

Student Administration will ask students to resubmit any dissertation which does not include the relevant cover page, declaration and proforma. If such a resubmission occurs after the deadline this will result in a late submission penalty.

This should list the contents in some sensible way.

Introduction

The introduction should explain the principal motivation for the project and show how the work fits into the broad area of surrounding computer science and give a brief survey of previous related work. It should generally be unnecessary to quote at length from technical papers or textbooks. If a simple bibliographic reference is insufficient, consign any lengthy quotation to an appendix.

Principally, this chapter should describe the work which was undertaken before code was written, hardware built or theories worked on. It should show how the project proposal was further refined and clarified, so that the implementation stage could go smoothly rather than by trial and error.

Throughout this chapter and indeed the whole dissertation, it is essential to demonstrate that a proper professional approach was employed.

The nature of this chapter will vary greatly from one dissertation to another but, underlining the professional approach, this chapter will very likely include a section headed "Requirements Analysis" and refer to appropriate software engineering techniques used in the dissertation. The chapter will also cite any new programming languages and systems which had to be learnt and will mention complicated theories or algorithms which required understanding.

It is essential to declare the starting point. This states any existing codebase or materials that your project builds on. The text here can commonly be identical to the text in your proposal, but it may enlarge on it or report variations. For instance, the true starting point may have turned out to be different from that declared in the proposal and such discrepancies must be explained.

Implementation

This chapter should describe what was actually produced: the programs which were written, the hardware which was built or the theory which was developed. Any design strategies that looked ahead to the testing stage should be described in order to demonstrate a professional approach was taken.

Descriptions of programs may include fragments of high-level code but large chunks of code are usually best left to appendices or omitted altogether. Analogous advice applies to circuit diagrams or detailed steps in a machine-checked proof.

The implementation chapter should include a section labelled "Repository Overview". The repository overview should be around one page in length and should describe the high-level structure of the source code found in your source code repository. It should describe whether the code was written from scratch or if it built on an existing project or tutorial. Making effective use of powerful tools and pre-existing code is often laudable, and will count to your credit if properly reported. Nevertheless, as in the rest of the dissertation, it is essential to draw attention to the parts of the work which are not your own. 

It should not be necessary to give a day-by-day account of the progress of the work but major milestones may sometimes be highlighted with advantage.

This is where Assessors will be looking for signs of success and for evidence of thorough and systematic evaluation. Sample output, tables of timings and photographs of workstation screens, oscilloscope traces or circuit boards may be included. Care should be employed to take a professional approach throughout. For example, a graph that does not indicate confidence intervals will generally leave a professional scientist with a negative impression. As with code, voluminous examples of sample output are usually best left to appendices or omitted altogether.

There are some obvious questions which this chapter will address. How many of the original goals were achieved? Were they proved to have been achieved? Did the program, hardware, or theory really work?

Assessors are well aware that large programs will very likely include some residual bugs. It should always be possible to demonstrate that a program works in simple cases and it is instructive to demonstrate how close it is to working in a really ambitious case.

Conclusions

This chapter is likely to be very short and it may well refer back to the Introduction. It might offer a reflection on the lessons learned and explain how you would have planned the project if starting again with the benefit of hindsight.

It is common, but not mandatory, to have a bibliography. Attention should be given to correct and consistent formatting.

It is common, but not mandatory, to have one or more appendices. Assessors like to see some sample code or example circuit diagrams, and appendices are the sensible places to include such items. Accordingly, software and hardware projects should incorporate appropriate appendices. Note that the 12,000 word limit does not include material in the appendices, but only in extremely unusual circumstances may appendices exceed 10-15 pages. If you feel that such unusual circumstances might apply to you you should ask your Director of Studies and Supervisor to discuss this with the Chairman of Examiners. Appendices should appear between the bibliography and the project proposal.

An index is optional.

A copy of the original project proposal must be included at the very end of the dissertation.

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How to do a Computer Science Thesis Tips

In a rapidly developing world, computer science is not standing still but constantly changing. Everyone sees the application of this science every day and practically in all areas. There are new technologies that push the existing ones.

That is why a lot depends on the right choice of the direction of your master thesis computer science. We want to give you a couple of useful tips on how to write a dissertation on computer science. Tips and Ideas Here!

· Choose the right theme. As a ship, you will name, so it will float! This initial stage of the thesis should be given attention and time. First, you need to understand which direction you are most interested in and like. Analyze what you can do in this direction and whether there is any sense in this. If you choose a direction in which you do not have enough knowledge and no interest, then with 100% probability, the process of writing a dissertation will become a nightmare for you. Therefore, pay enough attention and time to choose the computer science thesis topic that really suits you.

· Do not know where to start? You can go to your university and look through the theses to get inspiration. Consult your instructor who will push you to the right path. Think about what type of assignment you could expand in your dissertation.

· Pay attention to the relevant information selection. Often a student is faced with the fact that when searching for information on the Internet, valuable information is not taught. However, students decide to use it in their work or even copy, after which they often do not pass the anti-plagiarism check.

· Do not leave the dissertation written for the last moments. Often students first perform a practical part. And there is little time left for writing. Thoroughly plan the structure and gradually take notes. Since it will be much easier for you to create a whole structure.

· Change your attitude toward writing a computer science dissertation . Why should not you fulfill it in such a way that it will come in handy for you in the future? For example, write it in such a way that then it serves you a business plan and a push on the career ladder. It's so much more interesting, is not it?

Computer Science Thesis Topics and Areas

If you still do not know which direction you want to choose for your thesis, we offer you a list of topics that will be of use to you. Perhaps you will find exactly the topic you wanted, or maybe it will give you an understanding of which direction your thesis will be.

Some areas that include computer science:

· Artificial Intelligence

· Human-Computer Interaction

· Computer Graphics

· Databases/Information Retrieval

· Programming Languages

· Software Engineering

· Health Informatics

· Bioinformatics

· Symbolic Computing

· Algorithms & Complexity

· Networking/Communication

· Logic & Computation

· Systems Design

· Computer Security

Computer Science Theses and Dissertations topics:

1. How can programs reduce energy consumption in the world

2. Comparative analysis of storage architectures for the cloud: simple and cheap.

3. Study of existing methods of tracking mobile systems.

4. Exploring the search for an optimal system of safety. Which applications are safe for password management.

5. Exploring the Efficiency and Complexity of 3-Data Mining Alignments

6. Project Management: Tools and Technologies

7. Investigation of the improvement of the metadata scheduling algorithm in a robust environment.

8. Cipher text retrieval for cloud computing: secure and flexible data exchange.

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Thesis Helpers

Find the best tips and advice to improve your writing. Or, have a top expert write your paper.

105 Computer Science Thesis Topics And Writing Guide

After years of hard work and struggle, you have reached the most important stage of your academic life – writing a computer science thesis. It is clear that this is a defining moment for your life, and you wouldn’t want to throw anything to chance.

As a rule, most of the computer science theses consist of two major parts – writing a particular program and writing a paper, describing its functionality and the reasons behind its development.

Whether yours is a computer science bachelor thesis, computer science Master’s thesis, or a computer science Ph.D. thesis, you know it is not easy. With all the algorithms, binary equations, and programming calculations in your head, you might end up breaking down.

That calls for computer science help. Please wait a moment; I know what you are thinking. ‘Can I trust computer science help online for such a technical subject?’ Yes, you can! As you delve deep, you will realize why we are the best match for this kind of task.

Scroll down for more.

Computer Science Thesis Outline: How To Structure It?

Like any other academic research paper, a computer science thesis has a well-laid out structure that you will follow. An outline helps underpin the bulk of such a demanding paper into manageable parts.

Before we delve into this, we have to understand that there are various computer science fields such as:

Computer hardware systems Software systems Database systems Discrete mathematics Scientific computing

Therefore, whenever you determine the outline of your bachelor’s or master thesis computer science outline, bear those categories in mind. They will help you narrow down your research to a specific area, thus saving you time and energy too!

Depending on your institution, you will have a specified outline for your computer science thesis. However, the following parts form the standard outline of any thesis paper for Masters or Ph.D.

• Introduction (contains the background, statement of the problem, research questions, hypothesis, etc.)
• Next is the literature review , which gives the theoretical framework of your research
• The methodology section describes and justifies the methods to be used in data collection.
• The results and discussion section gives answers to your research questions and explains their meaning.
• Finally, the conclusion and recommendations review the findings and results and give a summary of the research.

The outline of a Master’s thesis in Computer Science or Ph. D. might vary depending on its requirements. Be sure to confirm with your professor on which outline to follow.

Master Thesis Computer Science Writing Guide

Writing such a large scale project is not something that can be done in a few days. The technicality of the computer science field makes it all the more complex. Some will tell you that it is more technical than coming up with a computer program.

That said, here are professionally handpicked tips for your Master Thesis in Computer Science:

• Understand the purpose of your computer thesis If you are writing on a computer program, show a deeper knowledge and understanding of the unique and fresh program. Let the reader see that you have mastered your program to the core.
• Begin writing early It is not something you can plan to do on the eve of the submission date. It will make your writing process light and highly motivational, especially with the voluminous books you will have to read.
• Selecting your topic It is a task that sends chills down the spine of many students. Thus, your topic should not be too narrow or too broad – this will portray you as an amateur. Draw your computer science thesis topic from something you encountered during your coursework.
• Keep reading To be precise, read a little, write a little, every day. It will surprise you how much ground you will have covered by the time you are submitting your thesis for review.

Latest Computer Science Thesis Topics For You!

Below is a comprehensive list of original computer science thesis topics for your inspiration:

• A case study of the pitfalls of assembly languages used to develop applications, websites, and software.
• Design and development of artificial intelligence systems
• Process improvement techniques for the functionality of robots
• An analysis of the factors that necessitate Java as one of the best programming languages
• What is the place of ethical hacking in today’s digital society?
• How to improve human-computer interaction
• What is the potential of computer systems in combating terrorism and crime?
• Identify how cyber-security enhances data confidentiality
• The design and engineering of computer applications and other systems
• Highlighting the differences between programming languages
• How can organizations make use of data mining?
• Identify efficient logistics in software architecture
• The effect of globalization and its impact on database administration
• A detailed investigation into the data availability and security
• The influence and impact of emerging computer technologies on the healthcare system
• Effect of training on knowledge performance in computer performance optimization
• The behavior of network architecture within a computing environment
• How can learning institutions implement computer systems for virtual and distance learning?
• Why risk management is necessary for data protection and information security in companies
• A detailed review of the role of education and industrialization on the development of computer systems.

From these topics, you can derive more computer science thesis topics for your presentation. Remember that the topic should be on a subject or field that is of interest to you. Settling on a complex and least researched topic might not be a good idea for you.

We can help you unearth more topics for your thesis paper. Read to the end to find out how?

Computer Science Thesis Topics

You need a computer science thesis topic before getting a computer science degree. Here is a list of interesting topics to create the best essay yet:

• Explain how to Blockchain benefits big businesses
• Discuss the conversation on using pet tracking chips
• Examine how genetic sequencing works using a computer
• How does IT help with security in financial institutions?
• Discuss what digitization means for privacy in the medical field
• What are the most effective ways to backup data in the medical field?
• Discuss the limitations of communication and computation
• Would you say the average ATM is secure?
• Analyze an innovation that seems threatening but seems to be a favorite for the human race
• Why should any business utilize open-source software, and how does it help with security?
• Discuss the role of technology in the classroom
• Discuss the personal or home use of quantum computers
• Would you say embedded systems are changing how the world works?
• What would you say about social media and technology trends
• Will technology reduce recruitment in an industry (of your choosing)
• How does technology affect human interactions, and will AI remedy that?
• Examine the computer assistance that can help businesses perform efficient customer care
• Analyze the technologies involved in casino live gambling
• Would you say artificial intelligence is a threat or blessing to contemporary society
• Explain if machine learning impact neurons and the way the brain works negatively
• How does Big Data help corporations
• Examine the average human’s knowledge of virtual reality through quantitative research
• Philosophize the future of technology
• Examine the future of programming languages and their efficiency
• What is the most creative development in computer technology yet?

Computer Science Topics

If you are fascinated by computer science and technology, you may want to conduct in-depth research into several fields. Here are interesting topics for a computer science thesis to review:

• Discuss databases, data mining, and how cryptocurrency works
• Examine the network between neuron network and machine learning
• How do robots and computers understand human language
• Examine the role of mathematics in modeling computers
• Discuss encryption and decryption of data
• How does computer-aided learning work
• How can you achieve usability in human-computer interaction
• Are there any hacking ethics?
• Discuss the advantages and disadvantages of the cloud storage
• What are the cybersecurity threats in banking systems
• Are there any loopholes in the technology of DAOs
• How does Blockchain Technology help the world
• Discuss the role of wireless systems in vehicles
• Examine how biometric systems work in cars
• Analyze how cryptography works.

Computer Science Research Topics

If you’ve ever wondered how technology and the world cooperate, here are some of the best topics to research and provide answers to for your essay or paper.

• What is the nexus of technology and finance?
• Examine the relationship between technology and healthcare
• Can robots work without any human intervention?
• How do computers interfere with forensics?
• Discuss computer security and information and how they work
• Examine the concerns of privacy in electronic health
• What are the vulnerabilities in bioinformatics?
• Explain the buildup of cyber-physical systems
• How has deep learning helped an industry of your choice
• What are the process computer take to analyze language
• Discuss the basic techniques for computer security
• Examine how natural language processing works
• Give an overview of textual mining
• How do deep visual models work?
• What is meant by distributed data clustering?

Research Topics in Computer Science

Computer science deals with how computer systems work. It is all about computer programs, strategies for development, and how they help humans. Here are 15 topics for you:

• Examine the role of computer technology in sports
• How does technology boost the performance of professional athletes?
• Would you say technology can lead to addiction?
• Explore the strategies used in gaming technology
• How does computer technology influence management solutions?
• Discuss the role of technology in the engineering field
• What is the future of information technology?
• What are the key developments and trends that show the vulnerabilities of technology?
• Using Tesla as a case study, what are technology’s vulnerabilities in automobile manufacturing and development.
• What does psychology say about the different Advancements in technology
• Examine the evolution of the gaming industry and how it has changed the perception of entertainment
• Track the evolution of the entertainment industry and technology has helped propel it
• What are the ways technology has propelled interactive media?
• Discuss the ways technology has influenced sports betting
• How has technology helped with fraud detection in the finance sector?

Computer Science Topics for Research

Being a computer science student means brainstorming, researching, and giving in-depth interpretations of why and how some things happen. Here are some relevant computer science research topics to steer your critical thinking skills:

• Analyze technological innovations in the construction and real estate industries
• Can AI have an impact on the economy of any country?
• Technology has helped with the way we understand the environment: argue
• Can technology help with how we solve the climate crisis?
• What is the role of technology in social media marketing?
• Discuss the technology companies like Google use to offer internet services
• Deeply analyze why some Mobile phones cannot work in the US
• How does the technology work in the creation of smart home systems?
• Data mining and ethical concerns: what are they?
• Will the 5-G network change how phones connect?
• Discuss the most important technology trends since COVID-19
• Why is facial scanning vulnerable to privacy breaches?
• How can computer technology help in tracking crime and offenders?
• What is the core buildup of math computing?
• Explain the most effective and ethical ways to tackle identity theft.

Computer Science Help Online For Master’s and PhD. Students

With all the tips and tricks above in mind, you might still need professional Computer Science thesis writing help . Does this make you an amateur or a lazy student? No! Getting such help will increase your knowledge base while sharpening your thesis writing skills. Iron sharpens iron, so they say.

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Computer Science & Engineering

Plan I: Thesis

M.S. Plan I - Thesis  

M.S. Plan II- Comprehensive Exam, Standard Option  

Plan I: Thesis 

Computer science or computer engineering, breadth   (12 units).

• Computer Science majors must take one course from  each of the three breadth areas: Theory, Systems, and Applications.
• Computer Engineering majors must take two courses from the Systems area AND one course from either Theory or Applications.
• Courses must be taken for a letter grade and completed with a grade of B- or higher.

DEPTH  (12 units)

• Computer Science majors must take three courses (12 units) from one depth area on this list.
• Computer Engineering majors must take three courses (12 units) from the Computer Engineering depth area only.
• Courses must be taken for a letter grade.
• CSE 203B-  Convex Optimization (*students that completed ECE273 or Math 245B will not be eligible to enroll in CSE 203B or count the course )
• CSE 234 -  Data Systems for Machine Learning
• CSE 250A  - AI: Probabilistic Reasoning and Learning
• CSE 251A - AI: Learning Algorithms
• CSE 251B - Deep Learning
• CSE 251C  -Machine Learning Theory
• CSE 251U (formerly CSE 291)  - Unsupervised Learning
• CSE 252D   - Advanced Computer Vision (Prof. Manmohan Chandraker's Section Only)
• CSE 254  - Statistical Learning
• CSE 255 -  Data Mining  and Analytics
• CSE 256  - Statistical Natural Language Processing
• CSE 257 - Search and Optimization
• CSE 258  - Recommender Systems and Web Mining
• CSE 275  - Deep Learning for 3D data (recently renumbered from CSE 291)
• CSE 291 - Advanced Data-Driven Text Mining
• CSE 291 - Structured Prediction for Natural Language Processing 
• CSE 291 - Deep Generative Models
• CSE 291 - Generative AI
• CSE 291 - Machine Learning for Robotics
• COGS 225  - Image Recognition (w/ Z. Tu)
• ECE 273  - Convex Optimization and Applications
• CSE 231  - Advanced Compiler Design
• CSE 237A  - Introduction to Embedded Computing
• CSE 237B  - Software for Embedded Systems
• CSE 237C  - Validation and Testing of Embedded Systems
• CSE 237D  - Design Automation and Prototyping for Embedded Systems
• CSE 240A  - Principles of Computer Architecture
• CSE 240B  - Parallel Computer Architecture
• CSE 240C  - Advanced Microarchitecture
• CSE 240D  - Application Specific Processors
• CSE 241A /ECE 260B   - VLSI Integrated Circuits & Systems Design
• CSE 243A  - Introduction to Synthesis Methodologies in VLSI CAD
• CSE 244A  - VLSI Test
• CSE 245  - Computer Aided Circuit Simulation and Verification  
• CSE 248  - Algorithmic and Optimization Foundations for VLSI CAD
• CSE 260  - Parallel Computation 
• CSE 291  - Memory/storage technologies and applications
• CSE 291  - Topics in Embedded Computing and Communication
• ECE 260A  - VLSI Digital System Algorithms & Architectures
• ECE 260C  - VLSI Advanced Topics
• ECE 284  - Special Topics in Computer Engineering 
• CSE 207B  - Applied Cryptography 
• CSE 221 - Operating Systems
• CSE 222A - Computer Communication Networks
• CSE 223B - Distributed Computing and Systems
• CSE 224 - Graduate Networked Systems
• CSE 227 - Computer Security 
• CSE 234 -  Data Systems for Machine Learning
• CSE 260 - Parallel Computation 
• CSE 262 - System Support for Applications of Parallel Computation 
• CSE 291  - Adv. Analytics & ML Systems
• CSE 291  - Adv. Topics in Classical Operating Systems
• CSE 291 - Blockchain
• CSE 291  - Cloud Computing
• CSE 291  - Cloud Application Dependability
• CSE 291  - Distributed Systems
• CSE 291 - Data Center Dependability
• CSE 291 - Internet Data Science for Cybersecurity
• CSE 291 -    Language Based Security
• CSE 291  - Operating Systems in Datacenters 
• CSE 291 - Quantum Computing System
• CSE 291  - Storage Systems
• CSE 291 -  Virtualization
• CSE 291-  Wireless and Communication/Internet of Things   
• CSE 232  - Principles of Database Systems
• CSE 232B  - Database System Implementation 
• CSE 233  - Database Theory
• CSE 234  -  Data Systems for Machine Learning
• CSE 291  - Management of Large-Scale Graph Data
• CSE 291 : Advanced Topic: Data Models in Big Data Era 
• CSE 163 - Advanced Comp Graphics
• CSE 168 -Cmp Graphics II Rendering
• CSE 252A - Computer Vision I
• CSE 252B - Computer Vision II
• CSE 252C - Selected Topics in Vision and Learning
• CSE 252D - Advanced Computer Vision
• CSE 270  - Discrete Differential Geometry
• CSE 272 - Advanced Image Synthesis
• CSE 273  - Computational Photography
• CSE 274 - Selected Topics in Graphics
• CSE 275  - Deep Learning for 3D data 
• CSE 291 -   Advances in 3D Reconstruction
• CSE 291 - Deep Learning for Sequences
• CSE 291 - Domain Adaptation in Computer Vision
• CSE 291 - Physical Simulation 
• COGS 260  - Image Recognition
• CSE 165 - VR User Interaction and Technology
• CSE 170/COGS 120  - Interaction Design
• CSE 210 - Principles of Software Engineering
• CSE 216/COGS 230  -  Topics in HCI
• CSE 217  - Human-Centered Computing for Health (HC4H)
• CSE 218  - Advanced Topics in Software Engineering
• CSE 276B - Human Robot Interaction
• CSE 276D - Healthcare Robotics
• CSE 291 - Anti-Social Computing (Vaccaro)
• CSE 291 - Critical Anaylsis and Computing (Pannuto)
• CSE 291 - Design and Deployment of Internet of Things Devices
• CSE 291  - Introduction to Computing Education Research
• CSE 291 - Programmers are People Too (Coblenz)
• CSE 291 -   Security, Privacy, and User Experience 
• CSE 291  - Towards Human-Centered Al
• CSE 291 - Usable Security and Privacy
• COGS 220  - Information Visualization 
• COGS 231 - (Design Seminar) Human Centered Programming (must be 4 units)
• COGS 234 (previously COGS 260) -  Foundations for Future User Interfaces
• COGS 260  - Crowdsourcing 
• DSC 291 - Privacy-sensitive Data Systems
• DSGN 201 - Design and Complex Sociotechnical Systems 
• ECE 284 : Mobile Health Device Design

EXCEPTIONS for Students that entered in fall 2022 or earlier ONLY:  CSE 291 - Social Computing  (Vaccaro),  CSE 291 -   HCI for Health,  CSE 250A  - AI: Probabilistic Reasoning and Learning

• CSE 210 - Principles of Software Engineering
• CSE 211 - Software Testing and Analysis
• CSE 218 - Advanced Topics in Software Engineering 
• CSE 230 - Principles of Programming Languages
• CSE 231 - Compiler Construction (formerly Advanced Compiler Design)
• CSE 291 -  Program Synthesis
• CSE 291 - Programmers are People Too (Coblenz)
• CSE 280A  - Algorithms in Computational Biology
• CSE 282  - Bioinformatics II: Sequence and Structure Analysis - Methods and Applications
• CSE 283  - Bioinformatics III: Functional Genomics
• CSE 284 - Personal Genomics 
• MATH 283  - Statistical Methods in Bioinformatics
• CSE 200  - Computability and Complexity
• CSE 201A  - Advanced Complexity
• CSE 202  - Algorithm Design and Analysis
• CSE 203A  - Advanced Algorithms
• CSE 203B - Convex Optimization Formulations and Algorithms
• CSE 205A  - Logic in Computer Science
• CSE 206A  - Lattice Algorithms and Applications
• CSE 207A  - Modern Cryptography 
• CSE 208  - Advanced Cryptography 
• CSE 291  - Communication Complexity
• CSE 291 - Quantum Complexity Theory
• CSE 291 - Semidefinite Programming & Approximation Algorithms
• CSE 291  -Topics in Advanced Cryptography

Exceptions for students that entered in fall 2021 or earlier:  CSE 207B  -  Applied Cryptography 

• CSE 276A  Introduction to Robotics

Select Two Courses from the following:

• CSE 276B  Human-Robot Interaction
• CSE 276C  Mathematics for Robotics
• CSE 276D  Healthcare Robotics 
• CSE 276E Robotic System Design and Implementation
• CSE 276F  Machine Learning for Robotics
• CSE 251A   AI: Learning Algorithms
• CSE 252B  Computer Vision II

ELECTIVES AND RESEARCH  (16 Units)

• A minimum of 8 and maximum of 12 units of CSE 298 (Independent Research) is required for the Thesis plan. 
• Courses must be completed for a letter grade, except the CSE 298 research units that are taken on a Satisfactory/Unsatisfactory basis..
• The remaining units are chosen from graduate courses in CSE, ECE and Mathematics, or from other departments as approved, per the ELECTIVES EXCEPTION LIST .
• A  Maximum of ONE undergraduate CSE upper-division course from approved ELECTIVES EXCEPTION LIST   is permitted towards Electives.
• Note, Graduate/Undergraduate Course Restriction policies below. In addition, seats are not guaranteed for approved list of CSE undergraduate course . Undergraduate students receive priority seating. Please direct questions regarding exception list to [email protected]
• These requirements are the same for both Computer Science and Computer Engineering majors.
• Seminar and teaching units may not count toward the Electives and Research requirement, although both are encouraged.

Graduate/Undergraduate Course Restrictions

• MS Students who completed one of the following six undergraduate versions of the course at UCSD are not allowed to enroll or count the graduate version of the course. For example, if a student completes CSE 130 at UCSD, they may not take CSE 230 for credit toward their MS degree.
• MS students may not attempt to take both the undergraduate and graduate version of these six courses for degree credit.  In order words, only one of these two courses may count toward the MS degree (if eligible under current breadth, depth, or electives).

CAPSTONE:  THESIS 

A thesis based on the student’s research must be written and subsequently reviewed by the student's MS thesis committee.  It is then submitted as described in the general university requirements.  The MS committee, appointed by the dean of Graduate Studies, consists of three faculty members, with at least two members from with the CSE department.

CSE 298 POLICIES

• CSE 298 is for thesis plan students with a confirmed thesis chair/advisor
• A minimum of 8 and maximum of 12 units of CSE 298 (Independent Research) is required for the Thesis plan
• CSE 298 is 4 units per quarter. If additional units are desired, a request for an exception can be sent by the thesis advisor/chair(s) via email to the CSE MS advisors.

MS Thesis Progress Report

• Student:  Thesis Progress Report Form For STUDENTS
• Thesis Chair or Co-Chair:  Thesis Progress Report form For THESIS ADVISOR

CSE M.S. Thesis - Planning Ahead Checklist

• Check Thesis Advisor Eligibility - email [email protected]
• Meet with Thesis advisor to understanding expectations and to be on the same page in terms of goals and completing all of the thesis requirements by the final graduating quarter
• Thesis Manual:   Thesis Formatting Manual
• For additional Formatting Resources:  Template page
• Meet with an MS academic advisor to plan ahead and understand the timeline and thesis submission requirements
• Establish Thesis Committee: With the guidance of your thesis advisor, establish thesis committee at least two quarters in advance of the final quarter. 
• Three committee members (which include the thesis chair) are required. All members must be eligible to serve on the committee (please email cse-ms-advisors with proposed faculty in advance to confirm and submit official committee to GEPA). Majority of the committee must be CSE eligible faculty (two of the three members. If thesis chair is not from CSE, CSE faculty co-chair will be required.
• Complete MS Candidacy/Degree Filing form (announced quarterly)
• Attend GEPA Thesis Formatting and Submission Session (announced quarterly)
• Student:  Thesis Progress Report Form For STUDENTS  (required)
• Thesis Chair or Co-Chair:  Thesis Progress Report form For THESIS ADVISOR  (required)
• Consult with MS Staff regarding timeline during final quarter for routing to committee thesis final report from (ahead of the final document review submission).
• REQUIRED: By week 1, schedule ahead both the preliminary appt with GEPA and final document review  ( https://gradforms.ucsd.edu/calendar/ )
• Note, for preliminary appt: For the preliminary appointment, a complete draft should be ready for GEPA to check the formatting. 
• The final review appointment should be scheduled for date that  after the official committee approval and before Friday of finals week.
• Committee Signatures and Docusign Timeline: A final report form will be initiated by the MS Staff via docusign to your committee, please make sure to communicate with the MS team regarding the form at the beginning of the quarter to ensure that you, the MS staff, and faculty have the correct timeline and dates for routing.
• Note: Final electronic version is submitted to ETD website www.etdadmin.com prior to final appointment. 

• UNIVERSITÄT HEIDELBERG
• Organization
• Research Groups
• Bachelor studies
• BSc 100% Computer Science
• BSc 50% Computer Science
• BSc 50% Computer Science Teaching
• Master studies
• Data and Computer Science
• Master of Education
• Subject Extension Master
• Expiring Programs of Study
• Announcements
• Highlights & Talks

The master's thesis is prepared as the final thesis of the master's degree and concludes with a final presentation. The master's thesis should show that the examinee is able to independently work on a problem in Computer Science or an application area using Computer Science methods within six months. The formal details of the master's examination are regulated by the examination regulations for the master's degree in Data and Computer Science in sections 17 ff (from page 13). The master's thesis covers 30 CP, and the final master's colloquium where you present the result of your thesis covers 4 CP.

Topic and Advisor

Start and Registration of Master's Thesis

Structure of the Thesis

Thesis Submission and Presentation

During your studies you will certainly develop an interest in certain areas of Computer Science. You should therefore plan your master's thesis early on (ideally from the 2nd semester) and take appropriate (in-depth) lectures, seminars or practicals in your area of ​​interest. The various working groups in Computer Science offer a wide range of courses. Approach an advisor early on and discuss possible topics, orientations and requirements for a master's thesis in the respective field; Of course, you can also make suggestions for a topic yourself. Please note that only lecturers from Computer Science (as listed in the working groups ) are authorized to formally serve as advisor for a master's thesis in Computer Science! 

External theses in a company or non-university institution require an advisor in Computer Science to supervise the work. So before you accept an external master's thesis, you should first clarify the supervision from the Computer Science side, i.e., look for a advisor in Computer Science!

Overall, you should start planning your master's thesis early and not only when you have completed all other academic work.

Andrea Piacquadio / PEXELS

Application Form for Master's Thesis

As noted above, you should deal with a topic and supervision for the master's thesis at an early stage. The basis for registering the thesis are the admission requirements as described in § 15 of the examination regulations . It is also advisable to clarify with the examination office when registering the final thesis whether the admission requirements have been met or whether all achievements have been entered correctly in the LSF .

The official registration of your master's thesis requires to fill out a form that can be found here , and that needs to be signed by you and your advisor and then is submitted to the examination office . You then have six month to complete and submit your thesis.

The period for writing the master's thesis can be extended once by a maximum of three months upon a justified application (e.g., illness) to the examination board. The application (Word document) must be approved by the supervisor and submitted to the examination office. The examination board will then review the application and inform you of the decision.

The structure of a master's thesis naturally varies from working group to working group. In any case, you should ask your supervisor for (good) example thesis from the working group so that you can get an impression of the structure, style, and scope. Many working groups also offer further information ("dos and don'ts") for writing master's theses. The following scheme serves as a guide for structuring a master's thesis:

• Heidelberg  University ( not University of Heidelberg! )
• <name of the institute>
• <name of the working group>
• Bachelor's Thesis
• <Title of the thesis>
• Name: <your name>
• Matriculation number: <matriculation number>
• Supervisor: <name>
• [optional] Second supervisor: <name>
• Date of submission: <date>
• No logos are allowed on the front page, not even that of the university !
• The signed declaration of independence on a new page
• Summary in German and English (each on a separate page)
• Table of Contents
• Chapter of the work with final bibliography and optional appendices.

fauxels /PEXELS

The completed master's thesis must be submitted to the examination office by the deadline in the form of a PDF file (via email to [email protected] ) and three printed copies (no ring binding; double-sided if preferred). For the formal details, see also § 18 of the examination regulations .

The master's thesis is presented as part of the master's colloquium . The colloquium should show that the person to be examined has sufficient knowledge of the basics of the topic of the thesis and related areas. As a rule, it must be completed no later than four weeks after submission of the thesis. Details on the bachelor's colloquium are regulated by § 19 of the examination regulations and must be discussed with your supervisor.

Please note that the master's colloquium will be made known to all students and lecturers in Computer Science. The announcement is made by the supervisor of the work at least one week before the presentation via the appropriate mailing lists.

As a rule, a certificate in German and English should be issued within two weeks after the evaluation of the last examination, i.e. the presentation, and receipt of the review by the thesis' advisor.

Master’s Thesis

Preliminary Note:  According to the Master regulations, the final paper in the Master program in Computer Science is the Master’s Thesis.

In a Master’s Thesis, candidates show their ability to independently perform scientific research on an appropriately challenging theme that also gives them the opportunity to develop their own ideas. On the basis of the "state-of-the-art" processes, the students must systematically apply the methods of computer science.

The Master’s Thesis must be written in the student's specialization area. The thesis advisor ensures that the objectives of the thesis can be reached within the intended time period. Advisors are available for consultation throughout the entire development of the thesis. They should regularly check that the work is progressing well and should also counteract any potentially negative developments, such as the student not meeting the objectives or exceeding the given time limit. They also give timely advice when the student is writing the thesis, and before the student submits the completed thesis.

All candidates must report the starting date of a Master’s Thesis to the Examination Office; the thesis topic and the starting date of the official processing period are then documented by the thesis advisor and forwarded to the Examination Office. The knowledge required for the thesis and how to acquire this knowledge should be clarified prior to when the topic is granted. For a Master’s Thesis, graduate students are first formally obliged to design a work plan. Approximately one month of full-time work (5 ECTS) is intended for this starting phase. The work plan (called a “Proposal”) must explore the thesis topic thoroughly enough and lay out a detailed plan for the following research on the thesis topic. The Proposal must explain this proposed research through detailed contents and depth as well as a complete depiction of the considered aspects. The Proposal must contain the following elements: a description of the task to be completed, the reasons behind working on the thesis, a clear formulation of the objectives, a description of the work necessary to reach the goal, and an accompanying timetable and preliminary outline of the written thesis. The work plan must be countersigned by the thesis advisor and submitted for approval to the Examination Office together with the application for the Master's Thesis. From this point on, the planned processing time is five months, whereas the start of the processing period agreed upon with the thesis advisor takes the one-month processing period for the work plan into account.

The written thesis is the main component of the final research. It should contain an incisive, understandable description of the completed research task, the research results, and the approach used to reach the result. In a thesis, candidates must also justify their decisions on which research methods or alternative solution approaches were used. The Master's Thesis must be written in the style of a scientific treatise. This includes in particular a summary, an outline, a description of the "state-of-the-art", and a bibliography of the literature used for the thesis. If software was designed and implemented during the thesis research, the structure, work methods and interfaces of the software must also be described precisely. Although it is not necessary to include the software documents in the written thesis, the software system, including the source code, must be available to the thesis advisor for review. Candidates must submit the written thesis in print to the examination office. Their advisor receives an additional copy in a common electronic format (PDF). 

The thesis defense, meaning an open-audience presentation followed by scientific discussion, is also an element of the Master’s Thesis. During the defense, the candidate must explain his/her research results concisely in a 30- to 45-minute presentation and then answer questions posed by a professional audience (usually during an advanced seminar held by the advisor). Ideally, the defense should be held soon after submission of the thesis.

To determine the grade granted for the thesis, the various achievements presented in the thesis are evaluated individually and internally. In general, the following individual achievements are divided into the categories listed below, arranged from the top down in order of the grade-relevant importance of the individual aspects.

Research Results . The results of the research work are given the highest priority and can come in various forms: theorems, software products, hardware products, empirically derived statements, or a mixture thereof. The approach employed to reach the results are also evaluated when the quality of the results are assessed.

Written Thesis. The written thesis, the main component of the research work, is given second priority. Here the evaluation includes determining how understandably graduates present the findings and research method to expert readers, and how well they concentrated on essential details and excluded non-essential details. The form, graphics, language and style of the thesis are also assessed.

Work method . The evaluation of the work method includes determining how purposefully and independently the candidate performed the research.

Presentation and discussion. Here, the committee evaluates the preparation of the presentation, the visual aids used for the presentation (such as slides), the candidates’ rhetorical skills and their ability to handle critical questions.

Due to the nature of the field of computer science, a Master’s Thesis that is written in cooperation with other institutes or (industrial) university-external parties is no rarity. And sometimes candidates write their thesis on a topic at an institute that corresponds to their minor subject. In both of these cases, the thesis advisor must inspect the research topic carefully and ensure that the candidate is given competent "on-site support". If the Master’s Thesis is written in a minor subject and an advisor in this minor subject takes on the role of the candidate’s supervisor, a university instructor in the Computer Science Department at the University of Paderborn must first determine that the research topic is plausible, and this instructor must supervise the thesis together with the advisor in the minor subject. Merely including the Computer Science Department advisor’s name as the secondary advisor when submitting the completed written thesis is not sufficient.

If the Master’s Thesis is written outside the university, such as at an external company, the thesis advisor must ensure that the candidate is not negatively affected by company-internal constraints (deadlines, financial dependence, non-disclosure agreements for concealing trade secrets). In this sense, “freedom of education” must be guaranteed. Companies are notified that the research work (the written thesis) is, by general rule, open to all readers. In special cases (such as when a patent is pending), a certain limited time period between the end of the research and the actual publication of the thesis can be determined. The in-company advisor/reviewer must make the entire research work available.

When submitting the thesis, candidates pledge to archive a public copy of the thesis for up to at least 5 years. The Computer Science Department, meaning the university in general, does not archive the submitted, accepted written thesis.

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Thesis Structure: Writing Guide For Your Success

If you are about to start writing your thesis, then it is extremely important to know as much as possible about the thesis structure. Learning the main thesis chapters should enable you to quickly structure your academic paper. Keep in mind that not structuring the paper correctly usually leads to severe penalties. We know some of you are probably having questions about numbering dissertation chapters. Basically, you just need to give all the major sections consecutive numbers. Use Arabic numerals (1, 2, 3, and so on). Check out the most frequently asked questions and them move on to the 7 parts of the thesis or dissertation structure.

Thesis Structure Frequently Asked Questions

• What is a basic good structure for a thesis? A: The best structure is the one listed below. It contains the 7 important parts any thesis should have.
• What does “the structure of this dissertation is in manuscript style” mean? A: It means that the thesis includes one or more manuscripts that have been written in a way that facilitates publication. The thesis can, in this case, be a collection of papers that have been written or co-authored by the student.
• Which chapters of dissertation are mandatory? A: All the 7 chapters below are necessary, if you want to get a top score on your paper.
• Where can I get a thesis structure template? A: You can quickly get a thesis structure example from one of our seasoned academic writers. Don’t base your thesis on mediocre samples you find online.
• What is the preferred thesis sentence structure? A: There is no set sentence structure that you have to follow. Just make sure your writing is organized in a logical manner and that all complex terms are explained the first time you use them.

Thesis Abstract

The first part of the thesis structure is the abstract. It is basically an overview of the entire paper. There is no set dissertation abstract structure. It is just a summary of your thesis and it should be just 200 to 300 words long.

Thesis Introduction

The introduction is one of the most important dissertation chapters. It should contain all of the following information:

A bit of background about the topic. Some information about the current knowledge. The aim of your research (the gap in knowledge that prompted you to write the thesis).

Remember that the introduction must present the thesis statement. It is very important to learn more about the thesis statement structure. A great thesis statement will pique the interest of the evaluation committee.

Thesis Literature Review

Many students who are looking to learn how to structure a thesis don’t know about the Literature Review section. Why? Because many people prefer to include it into the introduction. However, by separating the literature review from the intro, you can focus more on why your research is important. You can evaluate the most important research on your topic and clearly show the gap in knowledge.

Thesis Methods

In most cases, the Methods section is the easiest part of the structure of a thesis. All you have to do is present the method or methods you chose for the research. Don’t forget to also explain why you chose that specific research method. Your audience needs to understand that the chosen method is the best for the task.

Thesis Results

This is one of the most important chapters of a dissertation. In the Results chapter, you need to present your findings. Remember that written text is not enough. You need figures, stats, graphs, and other forms of data. This section contains all the facts of your research and should be written in an objective, neutral manner. It would be unusual for your to discuss your findings in this section.

Thesis Discussion

The Discussion chapter is very important in the dissertation chapters structure. It is the reason why you didn’t discuss your findings in the Results section. This is the section you can use to talk about your findings and provide your own opinions about the results. Here is what you can do in the discussion section:

Explain to the audience what your results mean for the scientific community. Comment on each of the results and discuss how your findings support your thesis. Explain any unexpected results so the evaluation committee can see that you know what you’re doing. Interpret the results and tie them with other research on the subject. How does your research help the academic community?

Thesis Conclusion

While not the most important chapter, the conclusion is one of the important chapters in a dissertation. It is the part where you can show your readers that you have achieved your research objectives. You can talk a bit about what you’ve learned in the process and even make some suggestions regarding the need for future research. In most cases, students also reiterate the thesis statement at the beginning of the conclusion, followed by a short summary of the paper’s most important chapters.

Still Not Sure How to Structure Thesis?

In case you are still struggling to find the best history dissertation structure, you should get some help as fast as possible. Remember that writing a thesis takes weeks, if not months. Don’t spend too much time trying to find the best structure. Instead, get in touch with a reliable academic company and get some quick assistance. For examples, one of our writers can create a thesis outline for you. You can just follow the outline and everything will be just fine.

Of course, you can also get some help with the thesis formatting. Citations and references can be difficult to master. Each academic writing style (MLA, Chicago, APA, etc.) has its own requirements. The way you format your academic paper is very important. Bolding and italicizing can emphasize certain ideas. A professional editor can help you make the thesis stand out from the rest. After all, a pleasantly-formatted dissertation that impresses the evaluation committee with its structure and quality of content has a very high chance of getting a top score.

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Computer Science Theses & Dissertations

Theses and dissertations published by graduate students in the Department of Computer Science, College of Sciences, Old Dominion University, since Fall 2016 are available in this collection. Backfiles of all dissertations (and some theses) have also been added.

In late Fall 2023 or Spring 2024, all theses will be digitized and available here. In the meantime, consult the Library Catalog to find older items in print.

Theses/Dissertations from 2023 2023

Dissertation: Inverse Mappers for QCD Global Analysis , Manal Almaeen

Thesis: Assessing the Prevalence and Archival Rate of URIs to Git Hosting Platforms in Scholarly Publications , Emily Escamilla

Thesis: Supporting Account-based Queries for Archived Instagram Posts , Himarsha R. Jayanetti

Dissertation: Detecting Malware With Securedeep Accelerator via Processor Side-Channel Fingerprinting for Internet of Things , Zhuoran Li

Dissertation: Tracing and Segmentation of Molecular Patterns in 3-Dimensional Cryo-ET/EM Density Maps Through Algorithmic Image Processing and Deep Learning-Based Techniques , Salim Sazzed

Dissertation: Towards Intelligent Runtime Framework for Distributed Heterogeneous Systems , Polykarpos Thomadakis

Theses/Dissertations from 2022 2022

Dissertation: Machine Learning-Based Event Generator , Yasir Alanazi

Thesis: Using Ensemble Learning Techniques to Solve the Blind Drift Calibration Problem , Devin Scott Drake

Dissertation: A Relevance Model for Threat-Centric Ranking of Cybersecurity Vulnerabilities , Corren G. McCoy

Dissertation: Evaluation of Generative Models for Predicting Microstructure Geometries in Laser Powder Bed Fusion Additive Manufacturing , Andy Ramlatchan

Thesis: TransParsCit: A Transformer-Based Citation Parser Trained on Large-Scale Synthesized Data , MD Sami Uddin

Dissertation: Towards Privacy and Security Concerns of Adversarial Examples in Deep Hashing Image Retrieval , Yanru Xiao

Theses/Dissertations from 2021 2021

Dissertation: MOVE: Mobile Observers Variants and Extensions , Ryan Florin

Dissertation: Improving Collection Understanding for Web Archives with Storytelling: Shining Light Into Dark and Stormy Archives , Shawn M. Jones

Dissertation: A Unified Framework for Parallel Anisotropic Mesh Adaptation , Christos Tsolakis

Theses/Dissertations from 2020 2020

Dissertation: MementoMap: A Web Archive Profiling Framework for Efficient Memento Routing , Sawood Alam

Dissertation: A Framework for Verifying the Fixity of Archived Web Resources , Mohamed Aturban

Thesis: Parallelization of the Advancing Front Local Reconnection Mesh Generation Software Using a Pseudo-Constrained Parallel Data Refinement Method , Kevin Mark Garner Jr.

Dissertation: Towards Dynamic Vehicular Clouds , Aida Ghazizadeh

Dissertation: Bootstrapping Web Archive Collections From Micro-Collections in Social Media , Alexander C. Nwala

Dissertation: Automatic Linear and Curvilinear Mesh Generation Driven by Validity Fidelity and Topological Guarantees , Jing Xu

Theses/Dissertations from 2019 2019

Dissertation: Expanding the Usage of Web Archives by Recommending Archived Webpages Using Only the URI , Lulwah M. Alkwai

Dissertation: Highly Accurate Fragment Library for Protein Fold Recognition , Wessam Elhefnawy

Dissertation: Scalable Parallel Delaunay Image-to-Mesh Conversion for Shared and Distributed Memory Architectures , Daming Feng

Dissertation: Aggregating Private and Public Web Archives Using the Mementity Framework , Matthew R. Kelly

Thesis: Enhancing Portability in High Performance Computing: Designing Fast Scientific Code with Longevity , Jason Orender

Thesis: Novel Use of Neural Networks to Identify and Detect Electrical Infrastructure Performance , Evan Pierre Savaria

Theses/Dissertations from 2018 2018

Dissertation: New Methods to Improve Protein Structure Modeling , Maha Abdelrasoul

Dissertation: Applying Machine Learning to Advance Cyber Security: Network Based Intrusion Detection Systems , Hassan Hadi Latheeth AL-Maksousy

Thesis: To Relive the Web: A Framework for the Transformation and Archival Replay of Web Pages , John Andrew Berlin

Thesis: Supporting Big Data at the Vehicular Edge , Lloyd Decker

Thesis: Deep Learning for Segmentation Of 3D Cryo-EM Images , Devin Reid Haslam

Dissertation: FlexStream: SDN-Based Framework for Programmable and Flexible Adaptive Video Streaming , Ibrahim Ben Mustafa

Thesis: Novel Technique for Gait Analysis Using Two Waist Mounted Gyroscopes , Ahmed Nasr

Dissertation: Leveraging Resources on Anonymous Mobile Edge Nodes , Ahmed Salem

Theses/Dissertations from 2017 2017

Dissertation: SenSys: A Smartphone-Based Framework for ITS applications , Abdulla Ahmed Alasaadi

Dissertation: ItsBlue: A Distributed Bluetooth-Based Framework for Intelligent Transportation Systems , Ahmed Awad Alghamdi

Dissertation: Finite Element Modeling Driven by Health Care and Aerospace Applications , Fotios Drakopoulos

Dissertation: Efficient Machine Learning Approach for Optimizing Scientific Computing Applications on Emerging HPC Architectures , Kamesh Arumugam Karunanithi

Thesis: Multi-GPU Accelerated High-Fidelity Simulations of Beam-Beam Effects in Particle Colliders , Naga Sai Ravi Teja Majeti

Theses/Dissertations from 2016 2016

Dissertation: Using Web Archives to Enrich the Live Web Experience Through Storytelling , Yasmin AlNoamany

Thesis: Magnopark, Smart Parking Detection Based on Cellphone Magnetic Sensor , Maryam Arab

Dissertation: Scripts in a Frame: A Framework for Archiving Deferred Representations , Justin F. Brunelle

Dissertation: Machine Learning Methods for Brain Image Analysis , Ahmed Fakhry

Dissertation: Novel Monte Carlo Methods for Large-Scale Linear Algebra Operations , Hao Ji

Dissertation: Machine Learning Methods for Medical and Biological Image Computing , Rongjian Li

Dissertation: Toward Open and Programmable Wireless Network Edge , Mostafa Uddin

Thesis: An Optimized Multiple Right-Hand Side Dslash Kernel for Intel Xeon Phi , Aaron Walden

Dissertation: Towards Aggregating Time-Discounted Information in Sensor Networks , Xianping Wang

Dissertation: A Computational Framework for Learning from Complex Data: Formulations, Algorithms, and Applications , Wenlu Zhang

Theses/Dissertations from 2015 2015

Dissertation: Efficient Algorithms for Prokaryotic Whole Genome Assembly and Finishing , Abhishek Biswas

Dissertation: De Novo Protein Structure Modeling and Energy Function Design , Lin Chen

Dissertation: High Performance Large Graph Analytics by Enhancing Locality , Naga Shailaja Dasari

Thesis: Avoiding Spoilers on Mediawiki Fan Sites Using Memento , Shawn M. Jones

Dissertation: Energy Harvesting-Aware Design for Wireless Nanonetworks , Shahram Mohrehkesh

Thesis: Parallel Two-Dimensional Unstructured Anisotropic Delaunay Mesh Generation for Aerospace Applications , Juliette Kelly Pardue

Dissertation: Detecting, Modeling, and Predicting User Temporal Intention , Hany M. SalahEldeen

Dissertation: Wireless Networking for Vehicle to Infrastructure Communication and Automatic Incident Detection , Sarwar Aziz Sha-Mohammad

Dissertation: Computational Development for Secondary Structure Detection From Three-Dimensional Images of Cryo-Electron Microscopy , Dong Si

Thesis: Mobile Cloud Computing Based Non Rigid Registration for Image Guided Surgery , Arun Brahmavar Vishwanatha

Theses/Dissertations from 2014 2014

Dissertation: Web Archive Services Framework for Tighter Integration Between the Past and Present Web , Ahmed AlSum

Dissertation: Modeling Stem Cell Population Dynamics , Samiur Arif

Dissertation: A Framework for Web Object Self-Preservation , Charles L. Cartledge

Dissertation: Document Classification in Support of Automated Metadata Extraction Form Heterogeneous Collections , Paul K. Flynn

Dissertation: Resource Allocation in Vehicular Cloud Computing , Puya Ghazizadeh

Thesis: Generating Combinatorial Objects- A New Perspective , Alexander Chizoma Nwala

Dissertation: Enhancing Understanding of Discrete Event Simulation Models Through Analysis , Kara Ann Olson

Dissertation: Scalable Reasoning for Knowledge Bases Subject to Changes , Hui Shi

Dissertation: Improving Structural Features Prediction in Protein Structure Modeling , Ashraf Yaseen

Thesis: Computational Analysis of Gene Expression and Connectivity Patterns in the Convoluted Structures of Mouse Cerebellum , Tao Zeng

Theses/Dissertations from 2013 2013

Thesis: HTTP Mailbox - Asynchronous Restful Communication , Sawood Alam

Dissertation: TDMA Slot Reservation in Cluster-Based VANETs , Mohammad Salem Almalag

Thesis: Protein Loop Length Estimation From Medium Resolution Cryoem Images , Andrew R. McKnight

Theses/Dissertations from 2012 2012

Dissertation: De Novo Protein Structure Modeling from Cryoem Data Through a Dynamic Programming Algorithm in the Secondary Structure Topology Graph , Kamal H. Al Nasr

Dissertation: FRIEND: A Cyber-Physical System for Traffic Flow Related Information Aggregation and Dissemination , Samy S. El-Tawab

Thesis: An Extensible Framework for Creating Personal Archives of Web Resources Requiring Authentication , Matthew Ryan Kelly

Thesis: Visualizing Digital Collections at Archive-It , Kalpesh Padia

Theses/Dissertations from 2011 2011

Dissertation: A Framework for Incident Detection and notification in Vehicular Ad-Hoc Networks , Mahmoud Abuelela

Dissertation: A Framework for Dynamic Traffic Monitoring Using Vehicular Ad-Hoc Networks , Mohammad Hadi Arbabi

Thesis: A Probabilistic Analysis of Misparking in Reservation Based Parking Garages , Vikas G. Ashok

Thesis: A Penalty-Based Approach to Handling Cluster Sizing in Mobile Ad Hoc Networks , Ryan Florin

Dissertation: Data Aggregation and Dissemination in Vehicular Ad-Hoc Networks , Khaled Ibrahim

Dissertation: Using the Web Infrastructure for Real Time Recovery of Missing Web Pages , Martin Klein

Theses/Dissertations from 2010 2010

Dissertation: A Virtual Infrastructure for Mitigating Typical Challenges in Sensor Networks , Hady S. Abdel Salam

Thesis: Merging Schemas in a Collaborative Faceted Classification System , Jianxiang Li

Thesis: XPath-Based Template Language for Describing the Placement of Metadata within a Document , Vijay Kumar Musham

Dissertation: Providing Location Security in Vehicular Ad Hoc Networks , Gongjun Yan

Theses/Dissertations from 2009 2009

Dissertation: Algorithms for Vertex-Weighted Matching in Graphs , Mahantesh Halappanavar

Theses/Dissertations from 2008 2008

Thesis: Using Timed-Release Cryptography to Mitigate Preservation Risk of Embargo Periods , Rabia Haq

Dissertation: Biology-Inspired Approach for Communal Behavior in Massively Deployed Sensor Networks , Kennie H. Jones

Dissertation: Biological Networks: Modeling and Structural Analysis , Emad Y. Ramadan

Dissertation: Integrating Preservation Functions Into the Web Server , Joan A. Smith

Theses/Dissertations from 2007 2007

Dissertation: FreeLib: A Self-Sustainable Peer-to-Peer Digital Library Framework for Evolving Communities , Ashraf A. Amrou

Thesis: Channel Management in Heterogeneous Cellular Networks , Mohammad Hadi Arbabi

Dissertation: Diagnosing Reading strategies: Paraphrase Recognition , Chutima Boonthum

Thesis: Investigating Real-Time Sonar Performance Predictions Using Beowulf Clustering , Charles Lane Cartledge

Dissertation: Lazy Preservation: Reconstructing Websites from the Web Infrastructure , Frank McCown

Theses/Dissertations from 2006 2006

Dissertation: Group Key Management in Wireless Ad-Hoc and Sensor Networks , Mohammed A. Moharrum

Dissertation: Template-Based Metadata Extraction for Heterogeneous Collection , Jianfeng Tang

Theses/Dissertations from 2005 2005

Dissertation: Collaborative Caching for efficient and Robust Certificate Authority Services in Mobile Ad-Hoc Networks , Laith Abdulaziz Al-Sulaiman

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Theses in the Department of Computer Science

Here you can find important information about theses in the department of computer science. [Photo: Pixabay]

The final thesis (Bachelor or Master) should show that the student is able to work independently on a complex task related to the study program and present it in a scientifically correct manner. It does not necessarily have to be the last module in the degree program, but there are guidelines as to when it can be started at the earliest (see Planning the Thesis).

In our study programs, there is no requirement that the thesis must be registered no later than X months after the last module exam. Nevertheless, please note that the thesis must be completed AND graded by the end of the maximum study period at the latest.

How does everything work around the thesis?

Requirements for the search for a topic.

• A thesis can only be started if at least 120 ECTS have been acquired in the Bachelor, and at least 60 ECTS in the Master. These ECTS must be entered on the transcript of records!
• The examiner of a thesis MUST be a professor of the Department of Computer Science. The examiner issues the topic and gives the final grade for the thesis.
• A second examiner (required for the master thesis) may come from another department / faculty of the University of Stuttgart.
• Often you will be assigned a supervisor who will give you advice and support and whom you can ask anything about your thesis. The supervisor is generally a member of the examiner's staff.
• It is possible to write a thesis in cooperation with a company. However, this is only possible if the examiner agrees. The company can at most take over the supervision, never the assignment of grades. However, since the orientation of the topics that come from companies often differs significantly from what is required as a thesis at the university, such constructs are very rare.

Finding a topic ...

To find a topic, it is best to contact the professors or their staff directly. Please make sure that you have taken courses from the department you are applying to. Otherwise, it may be difficult to work on a specific research topic of the department because you lack the prerequisites in this specific area. It may be a good start to take your own performance review and see what you particularly liked and where you also performed well on exams. These departments are then worth addressing first.

We try to post offers for theses as well as contact persons for the departments in ILIAS in the computer science marketplace.

If, after two to three months of intensive searching , you still have not found a topic, you can apply to the examination board for assignment of a thesis topic along with evidence of your unsuccessful search to date.

Registration of the thesis

It is important to note that you have to register your thesis with the Examinations Office no later than 1 month after starting the thesis (issue of the topic to you).

If a topic has been agreed upon, the secretary of the examiner prepares the computer science-specific contract including the license agreement (and, if applicable, confidentiality and/or language agreement) and hands out these documents to the student for proofreading. If possible, the time for proofreading and, if necessary, follow-up questions should not exceed one week. The contract documents are then signed by the student and returned to the secretary's office. If no publication is desired, the license agreement is crossed out. However, the document must remain with the contract.

At the same time, download the thesis application form from C@mpus. You can find it under the heading "My applications". If you are studying in the Master of Education, in the B.A. in Computer Science or in the B.A. minor in Computer Science, you will not receive this form from C@mpus, but directly from your exam officer. Please enter the following information in the form:

• the topic of the thesis in the original language and in English,
• the name of the examiner,
• the start date,
• sign the document and hand it in to the examiner's office.

The secretariat will have the document countersigned by the examiner and will then hand it back to you or send you a scan of it. You will then forward the document to the examination office as soon as possible. This can be done via the contact form and you can attach the scan or you can bring it personally to the examination office. There, the registration of the work will be entered into the system and confirmed on the form. Afterwards, please inform the examiner's office that the registration has been entered and that the work can now start. If the registration of the work is visible in the system (for the secretary's office), you will receive a copy of the contract.

By the way ...

• Theses can be registered at any time (even outside the exam registration period).
• In connection with the registration of the final thesis, the application for the issuance of the final documents must also be submitted. If you have any questions, please contact the examination office.

If you have any further questions, please contact the program manager or the examination board.

Submission of the thesis

The thesis must be printed and bound in the required number of copies (see contract). The following must be observed:

• For all printed copies, a rigid transparent film should be used as the front cover and, if possible, a black, solid cover at the back.
• The work must not be bound with a ring binding . Any type of adhesive or glue binding is permitted - preferably with a black linen booklet spine.
• The form requirements are summarized here once again.

To ensure that everything is printed, bound and handed in on time, you should collect the required number of covers from the examiner's office approximately 14 days BEFORE handing in your thesis.

In addition to the print copies the followings things have to be submitted:

• one separately printed title page of the thesis and
• the electronic version (pdf) of the thesis and an electronic version of the abstract in txt format. If you are studying in a German-language program and the thesis was written in English, both an English and a German abstract must be submitted. The electronic files can be sent to the examiner and the secretary's office by e-mail, on a stick or on a CD. The code generated by the work, if any, will be handed over separately to the examiner.

All printed copies and the electronic version must be handed in to the examiner's office by the deadline . After the examination by the secretary's office, you will receive the separate title page signed and date-stamped as proof of submission.

Form specifications, templates & links

Here are once again summarized all the notes (in German only)

• Instructions for examiners for the execution of theses
• Instructions for students
• Form specifications
• Template title page
• Template personal statetemt
• Graduation ceremony of the department

What if problems occur?

You forgot the register the thesis.

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Home > Engineering > Computer Science > Computer Science Graduate Projects

Computer Science Graduate Projects and Theses

Theses/dissertations from 2023 2023.

High-Performance Domain-Specific Library for Hydrologic Data Processing , Kalyan Bhetwal

Verifying Data Provenance During Workflow Execution for Scientific Reproducibility , Rizbanul Hasan

Remote Sensing to Advance Understanding of Snow-Vegetation Relationships and Quantify Snow Depth and Snow Water Equivalent , Ahmad Hojatimalekshah

Exploring the Capability of a Self-Supervised Conditional Image Generator for Image-to-Image Translation without Labeled Data: A Case Study in Mobile User Interface Design , Hailee Kiesecker

Fake News Detection Using Narrative Content and Discourse , Hongmin Kim

Anomaly Detection Using Graph Neural Network , Bishal Lakha

Sparse Format Conversion and Code Synthesis , Tobi Goodness Popoola

Portable Sparse Polyhedral Framework Code Generation Using Multi Level Intermediate Representation , Aaron St. George

Severity Measures for Assessing Error in Automatic Speech Recognition , Ryan Whetten

Theses/Dissertations from 2022 2022

Improved Computational Prediction of Function and Structural Representation of Self-Cleaving Ribozymes with Enhanced Parameter Selection and Library Design , James D. Beck

Meshfree Methods for PDEs on Surfaces , Andrew Michael Jones

Deep Learning of Microstructures , Amir Abbas Kazemzadeh Farizhandi

Long-Term Trends in Extreme Environmental Events with Changepoint Detection , Mintaek Lee

Structure Aware Smart Encoding and Decoding of Information in DNA , Shoshanna Llewellyn

Towards Making Transformer-Based Language Models Learn How Children Learn , Yousra Mahdy

Ontology-Based Formal Approach for Safety and Security Verification of Industrial Control Systems , Ramesh Neupane

Improving Children's Authentication Practices with Respect to Graphical Authentication Mechanism , Dhanush Kumar Ratakonda

Hate Speech Detection Using Textual and User Features , Rohan Raut

Automated Detection of Sockpuppet Accounts in Wikipedia , Mostofa Najmus Sakib

Characterization and Mitigation of False Information on the Web , Anu Shrestha

Sinusoidal Projection for 360° Image Compression and Triangular Discrete Cosine Transform Impact in the JPEG Pipeline , Iker Vazquez Lopez

Theses/Dissertations from 2021 2021

Training Wheels for Web Search: Multi-Perspective Learning to Rank to Support Children's Information Seeking in the Classroom , Garrett Allen

Fair and Efficient Consensus Protocols for Secure Blockchain Applications , Golam Dastoger Bashar

Why Don't You Act Your Age?: Recognizing the Stereotypical 8-12 Year Old Searcher by Their Search Behavior , Michael Green

Ensuring Consistency and Efficiency of the Incremental Unit Network in a Distributed Architecture , Mir Tahsin Imtiaz

Modeling Real and Fake News Sharing in Social Networks , Abishai Joy

Modeling and Analyzing Users' Privacy Disclosure Behavior to Generate Personalized Privacy Policies , A.K.M. Nuhil Mehdy

Into the Unknown: Exploration of Search Engines' Responses to Users with Depression and Anxiety , Ashlee Milton

Generating Test Inputs from String Constraints with an Automata-Based Solver , Marlin Roberts

A Case Study in Representing Scientific Applications ( GeoAc ) Using the Sparse Polyhedral Framework , Ravi Shankar

Actors for the Internet of Things , Arjun Shukla

Theses/Dissertations from 2020 2020

Towards Unifying Grounded and Distributional Semantics Using the Words-as-Classifiers Model of Lexical Semantics , Stacy Black

Improving Scientist Productivity, Architecture Portability, and Performance in ParFlow , Michael Burke

Polyhedral+Dataflow Graphs , Eddie C. Davis

Improving Spellchecking for Children: Correction and Design , Brody Downs

A Collection of Fast Algorithms for Scalar and Vector-Valued Data on Irregular Domains: Spherical Harmonic Analysis, Divergence-Free/Curl-Free Radial Basis Functions, and Implicit Surface Reconstruction , Kathryn Primrose Drake

Privacy-Preserving Protocol for Atomic Swap Between Blockchains , Kiran Gurung

Unsupervised Structural Graph Node Representation Learning , Mikel Joaristi

Detecting Undisclosed Paid Editing in Wikipedia , Nikesh Joshi

Do You Feel Me?: Learning Language from Humans with Robot Emotional Displays , David McNeill

Obtaining Real-World Benchmark Programs from Open-Source Repositories Through Abstract-Semantics Preserving Transformations , Maria Anne Rachel Paquin

Content Based Image Retrieval (CBIR) for Brand Logos , Enjal Parajuli

A Resilience Metric for Modern Power Distribution Systems , Tyler Bennett Phillips

Theses/Dissertations from 2019 2019

Edge-Assisted Workload-Aware Image Processing System , Anil Acharya

MINOS: Unsupervised Netflow-Based Detection of Infected and Attacked Hosts, and Attack Time in Large Networks , Mousume Bhowmick

Deviant: A Mutation Testing Tool for Solidity Smart Contracts , Patrick Chapman

Querying Over Encrypted Databases in a Cloud Environment , Jake Douglas

A Hybrid Model to Detect Fake News , Indhumathi Gurunathan

Suitability of Finite State Automata to Model String Constraints in Probablistic Symbolic Execution , Andrew Harris

UNICORN Framework: A User-Centric Approach Toward Formal Verification of Privacy Norms , Rezvan Joshaghani

Detection and Countermeasure of Saturation Attacks in Software-Defined Networks , Samer Yousef Khamaiseh

Secure Two-Party Protocol for Privacy-Preserving Classification via Differential Privacy , Manish Kumar

Application-Specific Memory Subsystem Benchmarking , Mahesh Lakshminarasimhan

Multilingual Information Retrieval: A Representation Building Perspective , Ion Madrazo

Improved Study of Side-Channel Attacks Using Recurrent Neural Networks , Muhammad Abu Naser Rony Chowdhury

Investigating the Effects of Social and Temporal Dynamics in Fitness Games on Children's Physical Activity , Ankita Samariya

BullyNet: Unmasking Cyberbullies on Social Networks , Aparna Sankaran

FALCON: Framework for Anomaly Detection In Industrial Control Systems , Subin Sapkota

Investigating Semantic Properties of Images Generated from Natural Language Using Neural Networks , Samuel Ward Schrader

Incremental Processing for Improving Conversational Grounding in a Chatbot , Aprajita Shukla

Estimating Error and Bias of Offline Recommender System Evaluation Results , Mucun Tian

Theses/Dissertations from 2018 2018

Leveraging Tiled Display for Big Data Visualization Using D3.js , Ujjwal Acharya

Fostering the Retrieval of Suitable Web Resources in Response to Children's Educational Search Tasks , Oghenemaro Deborah Anuyah

Privacy-Preserving Genomic Data Publishing via Differential Privacy , Tanya Khatri

Injecting Control Commands Through Sensory Channel: Attack and Defense , Farhad Rasapour

Strong Mutation-Based Test Generation of XACML Policies , Roshan Shrestha

Performance, Scalability, and Robustness in Distributed File Tree Copy , Christopher Robert Sutton

Using DNA For Data Storage: Encoding and Decoding Algorithm Development , Kelsey Suyehira

Detecting Saliency by Combining Speech and Object Detection in Indoor Environments , Kiran Thapa

Theses/Dissertations from 2017 2017

Identifying Restaurants Proposing Novel Kinds of Cuisines: Using Yelp Reviews , Haritha Akella

Editing Behavior Analysis and Prediction of Active/Inactive Users in Wikipedia , Harish Arelli

CloudSkulk: Design of a Nested Virtual Machine Based Rootkit-in-the-Middle Attack , Joseph Anthony Connelly

Predicting Friendship Strength in Facebook , Nitish Dhakal

Privacy-Preserving Trajectory Data Publishing via Differential Privacy , Ishita Dwivedi

Cultivating Community Interactions in Citizen Science: Connecting People to Each Other and the Environment , Bret Allen Finley

Uncovering New Links Through Interaction Duration , Laxmi Amulya Gundala

Variance: Secure Two-Party Protocol for Solving Yao's Millionaires' Problem in Bitcoin , Joshua Holmes

A Scalable Graph-Coarsening Based Index for Dynamic Graph Databases , Akshay Kansal

Integrity Coded Databases: Ensuring Correctness and Freshness of Outsourced Databases , Ujwal Karki

Editable View Optimized Tone Mapping For Viewing High Dynamic Range Panoramas On Head Mounted Display , Yuan Li

The Effects of Pair-Programming in a High School Introductory Computer Science Class , Ken Manship

Towards Automatic Repair of XACML Policies , Shuai Peng

Identification of Unknown Landscape Types Using CNN Transfer Learning , Ashish Sharma

Hand Gesture Recognition for Sign Language Transcription , Iker Vazquez Lopez

Learning to Code Music : Development of a Supplemental Unit for High School Computer Science , Kelsey Wright

Theses/Dissertations from 2016 2016

Identification of Small Endogenous Viral Elements within Host Genomes , Edward C. Davis Jr.

When the System Becomes Your Personal Docent: Curated Book Recommendations , Nevena Dragovic

Security Testing with Misuse Case Modeling , Samer Yousef Khamaiseh

Estimating Length Statistics of Aggregate Fried Potato Product via Electromagnetic Radiation Attenuation , Jesse Lovitt

Towards Multipurpose Readability Assessment , Ion Madrazo

Evaluation of Topic Models for Content-Based Popularity Prediction on Social Microblogs , Axel Magnuson

CEST: City Event Summarization using Twitter , Deepa Mallela

Developing an ABAC-Based Grant Proposal Workflow Management System , Milson Munakami

Phoenix and Hive as Alternatives to RDBMS , Diana Ornelas

Massively Parallel Algorithm for Solving the Eikonal Equation on Multiple Accelerator Platforms , Anup Shrestha

A Certificateless One-Way Group Key Agreement Protocol for Point-to-Point Email Encryption , Srisarguru Sridhar

Dynamic Machine Level Resource Allocation to Improve Tasking Performance Across Multiple Processes , Richard Walter Thatcher

Theses/Dissertations from 2015 2015

Developing an Application for Evolutionary Search for Computational Models of Cellular Development , Nicolas Scott Cornia

Accelerated Radar Signal Processing in Large Geophysical Datasets , Ravi Preesha Geetha

Integrity Coded Databases (ICDB) – Protecting Integrity for Outsourced Databases , Archana Nanjundarao

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Universities Have a Computer-Science Problem

The case for teaching coders to speak French

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Produced by ElevenLabs and News Over Audio (NOA) using AI narration.

Updated at 5:37 p.m. ET on March 22, 2024

Last year, 18 percent of Stanford University seniors graduated with a degree in computer science, more than double the proportion of just a decade earlier. Over the same period at MIT, that rate went up from 23 percent to 42 percent . These increases are common everywhere: The average number of undergraduate CS majors at universities in the U.S. and Canada tripled in the decade after 2005, and it keeps growing . Students’ interest in CS is intellectual—culture moves through computation these days—but it is also professional. Young people hope to access the wealth, power, and influence of the technology sector.

That ambition has created both enormous administrative strain and a competition for prestige. At Washington University in St. Louis, where I serve on the faculty of the Computer Science & Engineering department, each semester brings another set of waitlists for enrollment in CS classes. On many campuses, students may choose to study computer science at any of several different academic outposts, strewn throughout various departments. At MIT, for example, they might get a degree in “Urban Studies and Planning With Computer Science” from the School of Architecture, or one in “Mathematics With Computer Science” from the School of Science, or they might choose from among four CS-related fields within the School of Engineering. This seepage of computing throughout the university has helped address students’ booming interest, but it also serves to bolster their demand.

Another approach has gained in popularity. Universities are consolidating the formal study of CS into a new administrative structure: the college of computing. MIT opened one in 2019. Cornell set one up in 2020. And just last year, UC Berkeley announced that its own would be that university’s first new college in more than half a century. The importance of this trend—its significance for the practice of education, and also of technology—must not be overlooked. Universities are conservative institutions, steeped in tradition. When they elevate computing to the status of a college, with departments and a budget, they are declaring it a higher-order domain of knowledge and practice, akin to law or engineering. That decision will inform a fundamental question: whether computing ought to be seen as a superfield that lords over all others, or just a servant of other domains, subordinated to their interests and control. This is, by no happenstance, also the basic question about computing in our society writ large.

When I was an undergraduate at the University of Southern California in the 1990s, students interested in computer science could choose between two different majors: one offered by the College of Letters, Arts and Sciences, and one from the School of Engineering. The two degrees were similar, but many students picked the latter because it didn’t require three semesters’ worth of study of a (human) language, such as French. I chose the former, because I like French.

An American university is organized like this, into divisions that are sometimes called colleges , and sometimes schools . These typically enjoy a good deal of independence to define their courses of study and requirements as well as research practices for their constituent disciplines. Included in this purview: whether a CS student really needs to learn French.

The positioning of computer science at USC was not uncommon at the time. The first academic departments of CS had arisen in the early 1960s, and they typically evolved in one of two ways: as an offshoot of electrical engineering (where transistors got their start), housed in a college of engineering; or as an offshoot of mathematics (where formal logic lived), housed in a college of the arts and sciences. At some universities, including USC, CS found its way into both places at once.

The contexts in which CS matured had an impact on its nature, values, and aspirations. Engineering schools are traditionally the venue for a family of professional disciplines, regulated with licensure requirements for practice. Civil engineers, mechanical engineers, nuclear engineers, and others are tasked to build infrastructure that humankind relies on, and they are expected to solve problems. The liberal-arts field of mathematics, by contrast, is concerned with theory and abstraction. The relationship between the theoretical computer scientists in mathematics and the applied ones in engineers is a little like the relationship between biologists and doctors, or physicists and bridge builders. Keeping applied and pure versions of a discipline separate allows each to focus on its expertise, but limits the degree to which one can learn from the other.

Read: Programmers, stop calling yourself engineers

By the time I arrived at USC, some universities had already started down a different path. In 1988, Carnegie Mellon University created what it says was one of the first dedicated schools of computer science. Georgia Institute of Technology followed two years later. “Computing was going to be a big deal,” says Charles Isbell, a former dean of Georgia Tech’s college of computing and now the provost at the University of Wisconsin-Madison. Emancipating the field from its prior home within the college of engineering gave it room to grow, he told me. Within a decade, Georgia Tech had used this structure to establish new research and teaching efforts in computer graphics, human-computer interaction, and robotics. (I spent 17 years on the faculty there, working for Isbell and his predecessors, and teaching computational media.)

Kavita Bala, Cornell University’s dean of computing, told me that the autonomy and scale of a college allows her to avoid jockeying for influence and resources. MIT’s computing dean, Daniel Huttenlocher, says that the speed at which computing evolves justifies the new structure.

But the computing industry isn’t just fast-moving. It’s also reckless. Technology tycoons say they need space for growth, and warn that too much oversight will stifle innovation. Yet we might all be better off, in certain ways, if their ambitions were held back even just a little. Instead of operating with a deep understanding or respect for law, policy, justice, health, or cohesion, tech firms tend to do whatever they want . Facebook sought growth at all costs, even if its take on connecting people tore society apart . If colleges of computing serve to isolate young, future tech professionals from any classrooms where they might imbibe another school’s culture and values—engineering’s studied prudence, for example, or the humanities’ focus on deliberation—this tendency might only worsen.

Read: The moral failure of computer scientists

When I raised this concern with Isbell, he said that the same reasoning could apply to any influential discipline, including medicine and business. He’s probably right, but that’s cold comfort. The mere fact that universities allow some other powerful fiefdoms to exist doesn’t make computing’s centralization less concerning. Isbell admitted that setting up colleges of computing “absolutely runs the risk” of empowering a generation of professionals who may already be disengaged from consequences to train the next one in their image. Inside a computing college, there may be fewer critics around who can slow down bad ideas. Disengagement might redouble. But he said that dedicated colleges could also have the opposite effect. A traditional CS department in a school of engineering would be populated entirely by computer scientists, while the faculty for a college of computing like the one he led at Georgia Tech might also house lawyers, ethnographers, psychologists, and even philosophers like me. Huttenlocher repeatedly emphasized that the role of the computing college is to foster collaboration between CS and other disciplines across the university. Bala told me that her college was established not to teach CS on its own but to incorporate policy, law, sociology, and other fields into its practice. “I think there are no downsides,” she said.

Mark Guzdial is a former faculty member in Georgia Tech’s computing college, and he now teaches computer science in the University of Michigan’s College of Engineering. At Michigan, CS wasn’t always housed in engineering—Guzdial says it started out inside the philosophy department, as part of the College of Literature, Science and the Arts. Now that college “wants it back,” as one administrator told Guzdial. Having been asked to start a program that teaches computing to liberal-arts students, Guzdial has a new perspective on these administrative structures. He learned that Michigan’s Computer Science and Engineering program and its faculty are “despised” by their counterparts in the humanities and social sciences. “They’re seen as arrogant, narrowly focused on machines rather than people, and unwilling to meet other programs’ needs,” he told me. “I had faculty refuse to talk to me because I was from CSE.”

In other words, there may be downsides just to placing CS within an engineering school, let alone making it an independent college. Left entirely to themselves, computer scientists can forget that computers are supposed to be tools that help people. Georgia Tech’s College of Computing worked “because the culture was always outward-looking. We sought to use computing to solve others’ problems,” Guzdial said. But that may have been a momentary success. Now, at Michigan, he is trying to rebuild computing education from scratch, for students in fields such as French and sociology. He wants them to understand it as a means of self-expression or achieving justice—and not just a way of making software, or money.

Early in my undergraduate career, I decided to abandon CS as a major. Even as an undergraduate, I already had a side job in what would become the internet industry, and computer science, as an academic field, felt theoretical and unnecessary. Reasoning that I could easily get a job as a computer professional no matter what it said on my degree, I decided to study other things while I had the chance.

I have a strong memory of processing the paperwork to drop my computer-science major in college, in favor of philosophy. I walked down a quiet, blue-tiled hallway of the engineering building. All the faculty doors were closed, although the click-click of mechanical keyboards could be heard behind many of them. I knocked on my adviser’s door; she opened it, silently signed my paperwork without inviting me in, and closed the door again. The keyboard tapping resumed.

The whole experience was a product of its time, when computer science was a field composed of oddball characters, working by themselves, and largely disconnected from what was happening in the world at large. Almost 30 years later, their projects have turned into the infrastructure of our daily lives. Want to find a job? That’s LinkedIn. Keep in touch? Gmail, or Instagram. Get news? A website like this one, we hope, but perhaps TikTok. My university uses a software service sold by a tech company to run its courses. Some things have been made easier with computing. Others have been changed to serve another end, like scaling up an online business.

Read: So much for ‘learn to code’

The struggle to figure out the best organizational structure for computing education is, in a way, a microcosm of the struggle under way in the computing sector at large. For decades, computers were tools used to accomplish tasks better and more efficiently. Then computing became the way we work and live. It became our culture, and we began doing what computers made possible, rather than using computers to solve problems defined outside their purview. Tech moguls became famous, wealthy, and powerful. So did CS academics (relatively speaking). The success of the latter—in terms of rising student enrollments, research output, and fundraising dollars—both sustains and justifies their growing influence on campus.

If computing colleges have erred, it may be in failing to exert their power with even greater zeal. For all their talk of growth and expansion within academia, the computing deans’ ambitions seem remarkably modest. Martial Hebert, the dean of Carnegie Mellon’s computing school, almost sounded like he was talking about the liberal arts when he told me that CS is “a rich tapestry of disciplines” that “goes far beyond computers and coding.” But the seven departments in his school correspond to the traditional, core aspects of computing plus computational biology. They do not include history, for example, or finance. Bala and Isbell talked about incorporating law, policy, and psychology into their programs of study, but only in the form of hiring individual professors into more traditional CS divisions. None of the deans I spoke with aspires to launch, say, a department of art within their college of computing, or one of politics, sociology, or film. Their vision does not reflect the idea that computing can or should be a superordinate realm of scholarship, on the order of the arts or engineering. Rather, they are proceeding as though it were a technical school for producing a certain variety of very well-paid professionals. A computing college deserving of the name wouldn’t just provide deeper coursework in CS and its closely adjacent fields; it would expand and reinvent other, seemingly remote disciplines for the age of computation.

Near the end of our conversation, Isbell mentioned the engineering fallacy, which he summarized like this: Someone asks you to solve a problem, and you solve it without asking if it’s a problem worth solving. I used to think computing education might be stuck in a nesting-doll version of the engineer’s fallacy, in which CS departments have been asked to train more software engineers without considering whether more software engineers are really what the world needs. Now I worry that they have a bigger problem to address: how to make computer people care about everything else as much as they care about computers.

This article originally mischaracterized the views of MIT’s computing dean, Daniel Huttenlocher. He did not say that computer science would be held back in an arts-and-science or engineering context, or that it needs to be independent.

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Computer Science > Computer Vision and Pattern Recognition

Title: dvlo: deep visual-lidar odometry with local-to-global feature fusion and bi-directional structure alignment.

Abstract: Information inside visual and LiDAR data is well complementary derived from the fine-grained texture of images and massive geometric information in point clouds. However, it remains challenging to explore effective visual-LiDAR fusion, mainly due to the intrinsic data structure inconsistency between two modalities: Images are regular and dense, but LiDAR points are unordered and sparse. To address the problem, we propose a local-to-global fusion network with bi-directional structure alignment. To obtain locally fused features, we project points onto image plane as cluster centers and cluster image pixels around each center. Image pixels are pre-organized as pseudo points for image-to-point structure alignment. Then, we convert points to pseudo images by cylindrical projection (point-to-image structure alignment) and perform adaptive global feature fusion between point features with local fused features. Our method achieves state-of-the-art performance on KITTI odometry and FlyingThings3D scene flow datasets compared to both single-modal and multi-modal methods. Codes will be released later.

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