Department of Computer Science
The project system goes live on the date shown in the provisional timetable below. This does not mean you have to wait until then to start some preliminary groundwork on the module. As has been emphasized you are not bound to choose from the options that will be given. You are perfectly free (indeed, subject to the caveats outlined, encouraged) to develop your own project idea and solicit a suitable academic to act as the main supervisor.
Before ANYTHING AT ALL:
You can either propose a project by yourself or you select a project that is proposed by a member of staff. In either case, you are expected to show initiative and personal responsibility for your project.
The main aim of an MSc dissertation project is for a student to develop and demonstrate autonomy in the management and development of a realistic project in Computer science, either research- or application-oriented. Although new technical skills may be acquired, this is not the main aim. At the end of the project a student should have demonstrated the ability to initiate, plan, manage, and deliver a complete IT project for a customer or research supervisor. The delivery of the project will include giving interim presentations describing important stages of the project, and a final dissertation describing the project as a whole.
Projects often fail to be realistic in one of two contrasting ways: they are too trivial or too ambitious. Careful development of the Specification and Proposed Design will help identify, at an early stage, whether either of these are a risk.
Examples of Unrealistic Projects
Unsuitable, too trivial, failing to meet significant specified learning outcome criteria.
Unsuitable, too ambitious, aiming to complete (as a single individual) in three months development and delivery improving upon a system that has taken a team of several hundreds over a year to finalize.
According to the learning outcomes, the project must be a project in the domain of Computer Science that deals with a substantial IT problem for which solutions are implemented and tested. This does not automatically mean that the focus of the project is on the programming part, but it restricts the set of possible projects.
MSc projects are not necessarily expected to involve original research in the sense of making new scientific discoveries (this would be unrealistic). However, there should be some degree of scholarly added value attached to the project. Not in the sense of "what new subject a student may have learned from undertaking the project", but "what contribution does the project make to the knowledge of others", regardless of whether the project is a practical one or a research-oriented one, and whether or not is involves a large amount of programming or not.
Thus, MSc projects are not required to be fully-fledged research projects in their own right, but should add some seed of original thinking, innovative approach, interesting or beneficial contribution to the existing body of knowledge. The aim is not necessarily "to do something that has never been done before", but to present a new "angle" or "view point" on something that has been done before. For example:
Each project will be handled by a team of two academics:
Both supervisors assess the project (the second supervisor only assesses the second and third deliverable), monitor progress and give formative feedback.
Students are encouraged to propose their own projects. This is done by contacting a potential first supervisor directly via e-mail or MS Teams or a visit in person. All supervisors who list projects in the E-project system are potential first supervisors for student-proposed projects. Some other staff members not listed in the system could also be potential first supervisors. The list of potential supervisors is as follows.
IMPORTANT Please be aware that potential supervisors may be taking on different loads in terms of project offered/agreed. Should you have
a particular individual you would like to work with you are strongly encouraged to contact quickly. If you are proposing your own
project please provide as much detail as possible and be realistic about what can be feasibly accomplished within the project
timescale. (Equally, recalling that the project accounts for a significant contribution, try and ensure that any proposal involves an
amount of work commensurate with expectations).
A suitable supervisor can usually be found by having a look at staff members' websites available at https://www.liverpool.ac.uk/computer-science/staff. You should pay special attention to the topics of the person's recent publications and that they have at least some slight thematic overlap with your project. It is possible to have a first supervisor without having a thematic overlap, but this means that inevitably there will be less guidance available. If you cannot find a supervisor for your project, then you have to change the project.
Generally, projects are allocated on a first-come, first-served basis, but it is the discretion of the supervisor to make the final decision. It is expected that the number of MSc projects supervised/co-supervised by each academic is relatively balanced, so it is possible that a supervisor might turn down your request if they already have a sufficient number of projects taken up. If a first supervisor decides to supervise a project, they should enter the project into the E-Project System and record there (in the drop-down menu) that the student is allocated to that project. The second supervisor will be assigned automatically later, but staff members can also register themselves for being the second supervisor for specific projects once a project is in the E-Project System.
Whether the supervisory meetings are held in person or online and whether the assessments are held in person or online is decided by the supervisors and the student in agreement and is decided before the project starts.
A list of project suggestions will also be made available on the E-Project System in April during the current academic year. All students that have no project assigned at the deadline (see timetable) are assigned a random project from the list of remaining proposed projects, while taking into account their preference list that they set in the E-project system. Students are encouraged to finalise their project assignment before this step, so that they are guaranteed to have a suitable project. If you end up with a project that not suitable to your skill set, it will be very challenging for you to reach the learning outcomes.
One educational goal is to give the students the opportunity of making practical use of principles, techniques and methodologies acquired elsewhere in the programme. Although new technical skills may be acquired during the project duration, this is not the main aim.
If you select a project that is very far out of your area of expertise, for example if you select a project that involves a heavy programming load and you cannot program confidently in the required language, or if you select an AI project and this is your first contact with the technical details of AI, or if you select a networking research project without having the necessary background, then it will be very challenging to reach the learning outcomes, because there is not enough time in the project duration to acquire new complex technical skills on the required high level.
On the other hand, if you have the necessary technical background, then you are encouraged to propose (or choose from the list) a project that lets you apply your skillset in an area that you might be unfamiliar with, and pick up the necessary context during the early project weeks.
before Apr-24 (week 10 Semester 2) | You can already contact potential supervisors if you have an idea for your project |
Apr-24 - Apr-28 (week 10) |
Apr-24: Project topics are made available in the E-Project System Contact potential supervisors and propose a project to them or choose a project from the list |
May-01 - May-05 (week 11) | Contact potential supervisors and propose a project to them or choose a project from the list |
May-08 - May-12 (week 12; final teaching week of semester 2) | Contact potential supervisors and propose a project to them or choose a project from the list |
May-15 - May-19 (Exam Period Week 1) | Contact potential supervisors and propose a project to them or choose a project from the list |
May-22 - May-26 (Exam Period Week 2) | Contact potential supervisors and propose a project to them or choose a project from the list |
May-29 - Jun-02 (Exam Period Final week) | Last week to select a project. All other students are assigned a random project, taking into account their preference list (no guarantee). |
Jun-05 - Jun-09 (first week following end of Semester 2) |
Official project start: Jun-05 Background reading and literature review EXCEPTION: 31st July YinI students without secured placement. |
Jun-12 - Jun-16 | Background reading and literature review |
Jun-19 - Jun-23 | Development of project specification and proposed design |
Jun-26 - Jun-30 | Development of project specification and proposed design |
Jul-03 - Jul-14 |
Development of project specification and proposed design Specification and Design report and presentation slides deadline: Jul-14, 5:00pm 10 minute oral presentation of the specification and proposed design must be uploaded by this date EXCEPTION: 1st Sept 2023 17:00 YinI students without secured placement. |
Software implementation and testing EXCEPTION: 4th-8th Sept 2023 YinI students without secured placement. |
|
Jul-17 - Jul-21 | Software implementation and testing |
Jul-24 - Jul-28 | Software implementation and testing |
Jul-31 - Aug-04 | Software implementation and testing |
Aug-07 - Aug-11 | Software implementation and testing |
Aug-14 - Aug-18 | Software implementation and testing |
Aug-21 - Aug-25 |
Software implementation and testing Final presentation slides and demonstration video deadline: Sep-01, 5:00pm STATEMENT OF THE OBVIOUS Make sure you have uploaded BOTH slides and presentation video in advance of your scheduled meeting time. EXCEPTION: 3rd Nov. 2023 17:00 YinI students without secured placement. |
Aug-28 - Sep-01 |
To include
EXCEPTION: 6-10th Nov. 2023 YinI students without secured placement. |
Sep-04 - Sep-08 | Write-up of dissertation |
Sep-11 - Sep-15 | Write-up of dissertation |
Sep-18 - Sep-22 |
Write-up of dissertation Dissertation deadline: Sep-22, 5:00pm EXCEPTION: 1st Dec. 2023 5:00 pm YinI students without secured placement. |
If students fail one or more modules in the first and second semester examinations, then the following rules apply:
If you have failed 30 credits or more you will please need to confirm your intentions by completing an online form by Friday, 2023-Jul-14 (if you have failed 15 credits then you do not need to complete the form) and you must inform the COMP702 Module Co-ordinator, Prof. Paul Dunne (sq12@liverpool.ac.uk) and your supervisors of your decision for the project.
The extended deadlines are as follows.
Delayed projects | Deferred projects | ||
Final presentation slides deadline | Sep-08, 5:00pm | Nov-03, 5:00pm | |
Dissertation deadline | Oct-06, 5:00pm | Dec-01, 5:00pm |
Grade | Classification | Percentage | Qualitative Description |
---|---|---|---|
A* | Outstanding | 80-100 | Outstanding work. Factually almost faultless; clearly directed; logical; comprehensive coverage of topic; strong evidence of reading/research outside the material presented in the programme; substantial elements of originality and independent thought; very well written. |
A | Excellent | 70-79 | Excellent work. Logical; enlightening; originality of thought or approach; good coverage of topic; clear, in-depth understanding of material; good evidence of outside reading/research; very well written and directed. |
B | Very Good | 60-69 | Very Good work. Logical; thorough; factually sound (no serious errors); good understanding of material; evidence of outside reading/research; exercise of critical judgement; some originality of thought or approach; well written and directed. |
C | Good | 50-59 | Good work. Worthy effort, but undistinguished outcome. Essentially correct, but possibly missing important points. Largely derived from material delivered in the programme, but with some evidence of outside reading/research; some evidence of critical judgement; some weaknesses in expression/presentation. |
D | Marginal Fail | 40-49 | Inadequate work. Incomplete coverage of topic; evidence of poor understanding of material; poor presentation; lack of coherent argument. Very basic approach to a narrow or misguided selection of material. Lacking in background and/or flawed in structure. |
F | Fail | < 40 | Unsatisfactory work: Serious omissions; significant errors/misconceptions; poorly directed at targets; evidence of inadequate effort. Shallow and poorly presented work showing failure in understanding. |
In accordance with Appendix A, 2.1--2.3 of the Code of Practice on Assessment, a good knowledge of written English use must be demonstrated. This includes, minimally, correct spelling and grammar. You should also avoid over (and inaccurate) use of technical jargon (e.g. ``exponential increase'', ``decimate'') and the substitution of exotic polysyllabic constructions where simpler alternatives are available (e.g. ``do quickly'' is better than ``realise expeditiously'', use ``use'' not ``utilize''. In general, short simple words are better than involved lengthy equivalents. Similarly avoid cliche and hackneyed expressions where possible (e.g. ``state-of-the-art'', ``hot topic'', ''user friendly''
Basic proficiency in English will be a point considered in assessing written components of the project and misuse of English may have an effect on the mark given.
The University's standard policy on lateness penalties will be applied to the submission of any assessed coursework. See Section 6 of the Code of Practice on Assessment for further details.
For the Specification and Design oral presentation and for the Final Presentation the same rule is applied: the marker(s) may decide to penalise the student with 5 marks out of 100 if the presentation is in excess of the reserved time (excluding any time spent on questions from the markers).
Penalties will not reduce the mark below the pass mark for the assessment. Work assessed below the pass mark will not be further penalized for exceeding a presentation time limit or the electronic submission in an incorrect format.
The use of a compression format other than ZIP poses a serious risk that your work may not be marked at all. If we cannot decompress it, then we cannot read it!
By this stage of the project students should have completed the preliminary research and analysis required for the project and so have a clear (preliminary) idea of how they will carry out their project. Typically, this understanding will be recorded in a design using some standard methodology. The purpose of the two deliverables for this stage, a specification and design document, and a presentation, is to present this information both in written form and orally.
Your task is
A recommended structure for the document is as follows. The presentation should follow the same structure as the document, but focus on the most important elements of the design.
The following points also influence your mark:
The submission instructions are at the top of the assessments section.
This stage is intended to provide an overview of what has been achieved in the project. The purpose of the two deliverables for this stage, a short report and a presentation, is to summarise the main outcomes of the project. You should prepare (video using your presentation slides) a software demonstration illustrating the primary function(s) of the software.
Your task is
A recommended structure for the document is as follows.
The following points also influence your mark:
The submission instructions are at the top of the assessments section.
The purpose of the project dissertation is to provide a complete record of the work carried out by you during the course of the project. The dissertation is a record of what happened during the course of your project. It should detail (at an appropriate level) what was the purpose of your project, what was achieved, what software was designed (if applicable), what hypothesis was being tested (if applicable), experiments performed, data gathered, etc.
Your task is
A great deal of the background material in your introduction will have already been covered in your Proposed Specification and Design. It is okay to copy text and reuse your own material in the dissertation, although you might want to expand on it and discuss things in more depth.
The typical structure of the dissertation is outlined below (the exact content of these sections should not be consider "fixed", nor do they necessarily need to be in this order. This is just a suggestion of aspects of the project that you want to address in some manner in your dissertation).
The following points also influence your mark:
The submission instructions are at the top of the assessments section.
The main aims of this MSc-level module (from the module specification) are:
After completing the module students should be able to (from the module specification):
An excellent general book on how to tackle Computer Science projects is:
Dr Christian Dawson, Loughborough University
Projects in Computing and Information Systems: A Student's Guide, 3rd Edition
Pearson Higher Education, 2015.
ISBN 9781292081120
We have full-text as an online-ressource (but not for download) in the library.
There are many valuable writing guides, either in book form or on the WWW, one example is Postgrad.com. There, you can find information on: (i) study strategies, (ii) writing up your research, (iii) citing and documenting your sources, (iv) grammar and usage, and (v) theses and dissertations. You are encouraged to also use other sources --- look at computer science published journal and conference papers to get an idea of the required style. Remember that you are writing a scientific work and not an extended essay so do not be afraid of using lists, tables, diagrams, etc. --- whatever best gets your ideas across to the reader. However, try to be consistent in your approach to your project, and writing your dissertation.
It is good practice when undertaking a project to keep a log of your activities. This should provide a record of what you were doing and when, and record all key events in the project. A log book can also be valuable to help record potential ideas/avenues of exploration should time allow it (and when you are writing your dissertation, you can discuss these ideas as possible future work).
If you are conducting your project using your own computing facilities make sure you back up your work regularly. The Department cannot be held responsible if you lose all your work as the result of, for example, your laptop being lost or stolen, or a hard disk failure. Files on Departmental machines are backed up regularly by our technical staff and are therefore much safer.
Please familiarise yourself with University of Liverpool IT regulations and policies before utilizing any cloud-based repository for storage of programs and data.
If you have a technical question or request (like whether you can run specific software from the labs, or whether it is possible to use two seemingly incompatible applications) you are advised to contact the Computer Science Helpdesk (George Holt Building, 2nd floor, near the "blast door" between the Ashton and Holt Buildings). Please bear in mind that the Helpdesk has a busy schedule, so try to clarify your requirements in advance, so that time and resources allow to look for alternatives.
You need to conduct your project in compliance with the British Computer Society (BCS) Code of Conduct. As part of your dissertation, you will need to discuss how your project and its conduct relate to this Code.
Please bear in mind that for projects that involve the collection of data from people, this must be done in an ethical manner. Collection of such data must be approved before any collection is performed. See the secion on Ethical Use of Human Data. The use or collection of human data (not in the public domain) without ethics approval could constitute research misconduct.
Related project information can be also found here.
All students should be aware that they are responsible for what they write. One of the pillars of progress in research is that authors can benefit from each other's earlier work. Arguments made in a dissertation should be supported by facts. One way of doing this is to refer to the existing body of work. For example one can argue that X is true because Y and Z demonstrated it was true in a number of articles published in reputable journals (and then give references to the publications in question). If readers want to disagree with you they also have to take issue with X and Y!
However, it is important for students to make clear, when writing their dissertation, what their original contribution is and what is not. If a student is unable to make a point more clearly than a source that they have found (a book, a paper, or a document on the web), they should use quotations: put the quoted sentence(s) in between quotes " and ", and make clear in the running text where the reference is taken from. Then, cite that source in your bibliography and/or list of references. There are many standards to do citation, students are free to use any style, but should make sure that they make citations in a consistent way.
It does not make sense to quote more than 3 or 4 sentences at one occasion. If readers really have to literally read another source, students should tell them in their introduction, and say that they assume that the reader has read that source before starting reading the student's dissertation.
Apart from using somebody else's text, students may also come across figures, pictures, and diagrams which they think illustrate their point better than they could do otherwise. Again, if this is the case (and students should first check that they are not acting against any copyright law), students should state that the figure/picture/diagram is taken from a particular source, and give the full details of that source in their bibliography.
For projects that utilize data (e.g. to formulate or test hypotheses), data must not be fabricated to conceal a paucity of legitimate data, nor should legitimate data be altered, enhanced or exagerrated to mislead the reader.
For more information, see the University's Code of Practice on Assessment. See also Appendix L of the Code of Practice on Assessment for definitions of plagiarism and collusion, and the penalties for those actions.
Students are expected to read, understand, and follow this Code of Practice on Assessment. Note that when you submit your assessments through the Departmental Submission Server, you are also making a Declaration on Plagiarism, Collusion, and Fabrication of Data (i.e. that the work you submit is your own work, or properly attributed where appropriate, and the data you supply has not been improperly fabricated or altered).
Some MSc projects could make use of human subjects and/or data about people. When conducting research involving human participants or personal information, it is important that the research is conducted in line with ethical research principles. Under the University's policy on research ethics, all research projects which involve human participants, human tissues, or personal information should receive formal ethical approval before they commence, unless:
The first supervisor of the project should obtain ethical approval prior to the use of human subjects or human data. Using human subjects/human data without ethics approval could constitute research misconduct. Here is the flow chart for the University Ethics Approval Process. This approval process is performed online.
Ethical approval is not required to use data from Twitter as long as the Twitter data is available in the "public domain". Twitter ids should be anonymised (e.g. hash Twitter handles to some other string) when doing so will not violate Twitter's Terms and Conditions.
Note that if ethical approval is necessary, this must be obtained before collection of data begins. Without approval, inappropriate collection/use of data could constitute research misconduct.
The use of artificial data (say, for testing purposes) is allowed, provided that practice is explicitly declared. (It is often common practice to generate data according to a probilistic distribution for testing algorithms/software.) In the case that you do this, you should clearly state how the data was generated, which tests were performed using this artificial data, etc.
Almost all software needs to be tested and evaluated by human participants. Usually this will be family and friends, but if you need a larger pool of people, make sure you recruit and treat them ethically.
Participant data includes the details of people who test and evaluate your software, questionnaire results, interview transcripts, photos of people, and audio/video recordings of the evaluation. Such data should always be treated according to the following rules.
When you write your dissertation you will probably want to include text and comments from participants. In all cases this should be anonymised, and you should make sure you have their permission to use what they said. You should not use any comments that could inadvertently identify anyone.
Since the project module spans such a long time and since time management is one of the module's learning outcomes, running out of time is not an acceptable reason to request an extension. You should be having regular progress meetings with your supervisor. Plan ahead to make sure you submit on time. Supervisors cannot grant extensions. If you have extenuating circumstances you can request an Exemption from Late Penalties. Please contact the Student Experience Team for help and advice.