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1. OVERVIEW

COMP702 is the MSc 60 credit project module that will run over the summer from the week after the semester 2 exams to (roughly) one week before the start of the next academic year.

A student is expected to spend approximately 600 hours over the course of the project period for research, development of solutions, writing assessments, implementation of solutions (e.g. programming, where appropriate), performing experiments/empirical investigations to gather data (again, where appropriate), etc.

This web page is designed to offer specific guidance about the conduct of MSc projects within the Department of Computer Science at the University of Liverpool.

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1.1. Supervision

Each project will be handled by a team of two academics:

• Supervisor: This person is expected take the lead in supervising the student. The supervisor will typically propose the original project and should meet the student on a regular basis throughout the project to offer guidance, support and advice.
• Second Supervisor: This person should provide back-up to the supervisor. The second supervisor should have some expertise in the topic area, and be able to provide back-up support and guidance for the student, particularly at times when the first supervisor is away (as is typical over the summer).

Both supervisors will also act as the assessors of the project, to monitor progress and to give formative feedback.

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1.2. MSc Electronic Project System

The assessment process will be supported by the e-Project System. Documents submitted via the Departmental Submission System will show up on the e-Project System, and students will be able to see assessment results from the two supervisors on that system. Note that the e-Project System is accessed using your login credentials from the Computer Science Department.

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2. BASIC PHILOSOPHY

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.

With reference to:

1. The masters qualification descriptors in the Framework for Higher Education Qualifications in England, Wales and Northern Ireland (FHEQ),
2. The QAA benchmark statement for Masters degrees in Computer Science, and
3. The so-called Dublin Descriptors in the (May 2005) Framework for Qualifications of the European Higher Education Area (EHEA),

there is a requirement that the dissertation should be intellectually demanding and involve the original application of knowledge gained in the programme of study.

Level M Projects are not necessarily expected to involve original research in the sense of making new scientific discoveries (this would be unrealistic). However, at level M 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 the project makes to the knowledge of others") regardless of whether the project is a practical one or a research-oriented one.

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:

1. The critical comparison of some complimentary recent innovations.
2. The extension or adaptation of some recent innovation so that it becomes in some sense better, e.g. faster, more accurate, requires less storage, etc.
3. The application of some recent innovation to a generic application area where it has not yet been applied.
4. The combination/concatenation of some recent innovations in a novel manner not previously recorded in the literature.

Whatever the case, the key characteristics of the work carried out should be:

• Originality: Originality in the application of knowledge, together with a practical application of techniques of research and enquiry.
• Generalization: Even when the project has a very specific target, students should address it in a way which will make the results potentially applicable in a broader context.
• Critical evaluation: Design decisions made by students in the course of the project should be made in the context of a critical examination of alternatives, and the students should subject their results and conclusions to the same rigorous analysis.

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2.1. Formal Objectives

The aims of the module (from the module specification) are:

1. To give students the opportunity to work in a guided but independent fashion to explore a substantial problem in depth, making practical use of principles, techniques, and methodologies acquired elsewhere in the programme.
2. To give experience of carrying out a large piece of individual work and in producing a dissertation.
3. To enhance communication skills, both oral and written.

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2.2. Learning Outcomes

After completing the module students should be able to:

• Investigate and specify a substantial problem in the domain of Computer Science, to place it in the context of related work including, as appropriate, Computer Science research, and to produce a plan to address this problem;
• Make use of the qualities and transferable skills necessary for the conduct of a Computer Science project: (i) the exercise of initiative and personal responsibility; (ii) decision making in complex situations; (iii) risk identification (including, as appropriate, commercial and scientific risk), assessment, and control; and (iv) the independent learning ability required for continuing professional development;
• Demonstrate effective time management, self-direction and originality in carrying out a project in the domain of Computer Science;
• Locate and make use of information relevant to a given IT project;
• Design a solution to a substantial IT problem;
• Implement and test potential solutions to IT problems;
• Evaluate critically, as relevant to the project, current research and advanced scholarship in Computer Science, and evaluate their own work;
• Conduct and evaulate critically the project within the professional, legal, social, and ethical framework in Computer Science and Software Engineering;
• Prepare and deliver formal presentations;
• Prepare and deliver a demonstration of software;
• Structure and write a dissertation describing their project.

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3. SUGGESTED PROJECTS

A list of suggested projects will be made available on the e-Project System in April during the current academic year.

During a specific timeframe, students will select a project by contacting supervisors directly (use e-mail, or visit in person). 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 she/he already has a sufficient number of projects taken up.

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4. CONDUCT OF PROJECT

4.1. Reading

An excellent general book on how to tackle Computer Science projects is:

Christian W. Dawson, "Computing Projects: A Student's Guide", Prentice Hall, 2000.

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4.2. Writing style

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.

A LaTeX dissertation template is available, with a PDF file to show what it looks like. Note that the section headers and such provided are only examples.

A Word template is also available that students may use if they wish. This template is reproduced here by permission of Laureate Online Learning, the University of Liverpool's eLearning partner.

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4.3. Log Books

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).

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4.4. Technical Support

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.

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4.5. Professional Issues

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 associated webpage 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.

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5. TIMETABLE FOR SUMMER/AUTUMN 2021

5.1. Assessment stages

An overview of the assessment stages is presented in Table 1. All assessments are done by two markers, typically the 1^st and 2^nd supervisors. Each of the components of assessment will be graded using the CS Department's standard MSc grade descriptors, i.e., assessors will attempt to assign grades which most closely correspond to the marking descriptors that are shown on each assessment's descriptive page.

Table 1: COMP702 project assessment stages

Activity	Mode	Deliverables	# marks (%)
Specification and Proposed Design	Report and Oral presentation	Short report (recommended ≤10 sides A4) and copy of slides submitted via the Coursework Submission System.	20
Final presentation	Report and Oral presentation (incl. software demo)	Short report (recommended ≤10 sides A4) and copy of slides submitted via the Coursework Submission System.	20
Dissertation	Written work	Electronic version submitted via the Coursework Submission System.	60

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5.2. Timetable of activities

Table 2 shows a suggested timetable of activities as well as important dates related to the project.

See the next section if you have two or more re-sit exams.

Table 2: COMP702 Project Timetable

Important Date	Activity
Monday 7 June 2021	MSc projects officially begin (Week 1).
Weeks 1 and 2	Background reading and literature review.
Weeks 3, 4 and 5	Development of project design.
Friday 9 July 2021 (5:00pm) (to turn in Specification and Design report)	Specification and Proposed Design report (end of Week 5). Oral presentation (by end of Week 6 (July 12-16)).
Weeks 6, 7, 8, 9, 10, 11, and 12	Software implementation and testing.
Friday 27 August 2021 (5:00pm)	Final presentation + software demo when appropriate (by end of Week 13 (Aug 30 - Sep 03)).
Weeks 11, 12, 13, and 14	Software experimentation and analysis of results.
Weeks 13, 14, and 15	Write-up of dissertation.
Friday 24 September 2021 (5:00pm) (noon)	Dissertation hand in (Friday in Week 16, Firm deadline).

Note: Given the nature of the MSc projects and because staff are likely to be absent over some of the summer period, there is some flexibility regarding dates for the oral presentations and the demonstration. However, despite changes to the exact date of a presentation, you must still submit any documents/presentation slides by the required deadline (unless an extension has been agreed beforehand).

Your dissertation, and, where appropriate, source code of all software produced, must be submitted via the Coursework Submission System by Friday 24 September 2021 (5:00pm).

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5.3. Students with resit exams

IMPORTANT NOTE!!! We apply the following rules in relation to resit exams:

• Students who failed 15 credits proceed as normal with their project;
• Students who failed 30 credits (or more) can proceed as normal with their project, but have the option to defer the implementation and write-up stages (only!) of the project until after their resit exams. Students will need to make this decision within two weeks of the second semester exam results being published and inform the COMP702 module co-ordinator and supervisors of their decision to proceed (with extensions as above), or to defer their project. Non-EU students should note that deferring the project could have obvious implications with regards to your visa (for which you are responsible to check and act accordingly).
  
  If a student decides to proceed as normal with their project, then an extension (of two weeks) to the deadlines for the implementation (i.e. the final presentation/demonstration) and dissertation stages on the project will be granted (only those final two stages have the two week extension).
  
  For students who defer the implementation and write-up stages of the project, the deadlines for the final presentation/demonstration and the dissertation are given in Table 3 below.

Table 3: Project deadlines for students with multiple re-sits

Activity	Two Week Extension	Deferred Projects
Final presentation	Friday 17 September 2021 (5:00pm) (Presentation: Week 20-24 September 2021)	Friday 5 November 2021 (5:00pm) {Presentation: Week 8-12 November 2021)
Dissertation	Friday 8 October 2021 (5:00pm)	Friday 3 December 2021 (5:00pm)

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6. ACADEMIC INTEGRITY

All student 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. See also the next section on Use of Data with regards to the type of data you can use.

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).

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7. USE OF DATA

For projects that utilize human participants (as subjects) or real human data, it is possible that ethical approval of the use of such data is required. Your first supervisor should have obtained ethical approval for the use of such data before the project begins.

See the page on Ethical use of human data for more details, including some comments about the use of data obtained from Twitter.

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.

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8. RECOVERY OF PROBLEM PROJECTS

A small number of projects may have difficulties, particularly in the early stages. Appropriate action will be suggested for all projects which score below grade C on any of the assessment stages. Specific actions may be recommended for other projects also.

IMPORTANT WARNING: 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 read and understand the University's Code of Practice for Using Cloud Services before utilizing any cloud-based repository for storage of programs and data. Storing data on a service such as DropBox may violate the Information Security Policy of the university.