Computer Science BSc

Spending four hours a week in lectures and computer classes, you’ll cover the following topics:

• security of the computer
• security of networks
• security and the internet
• software and hardware security
• mobile security
• basic cryptography

This module looks broadly into professional ethics within the scope of the computing discipline. It covers a range of professional, ethical, social and legal issues in order to study the impact that computer systems have in society and the implications of this from the perspective of the computing profession. In particular, the module covers topics such as introduction to ethics, critical thinking, professionalism, privacy, intellectual and intangible property, cyber-behaviour, safety, reliability accountability, all these within the context of computer systems development.

This module examines how knowledge can be represented symbolically and how it can be manipulated in an automated way by reasoning programs.

Some of the topics you’ll cover include:

• first order logic
• resolution
• description logic
• default reasoning
• rule-based systems
• belief networks

You’ll look at the development of software applications for mobile devices, with a practical focus on the Android operating system. You’ll consider and use the software development environments for currently available platforms and the typical hardware architecture of mobile devices. You’ll spend around three hours per week in lectures and computer classes.

In this module, you will consider the design of collaboration and communication technologies used in a variety of different contexts including workplace, domestic and leisure environments. You will consider the basic principles of such technologies, explore the technologies from a social perspective, consider their impact on human behaviour and critically reflect on their design from a human-centred perspective.

You are given the opportunity to combine your developing CCT knowledge with your programming abilities. You have the whole semester to build a working collaborative project either individually, or you can opt to work in a team, and produce a report on how it supports collaboration according to CCT theory. The primary focus is on building a working application, and so existing strong programming ability is required. 

You’ll examine aspects of language and compiler design by looking at the techniques and tools that are used to construct compilers for high level programming languages. Topics covered include: parsing; types and type systems; run-time organisation; memory management; code generation; and optimisation. You’ll spend around four hours each week in lectures and computer classes. 

You will begin by considering the attempts to characterise the problems that can theoretically be solved by physically possible computational processes, along with the practical implications. You will then consider the area of complexity theory, looking at whether or not problems can be solved under limitations on resources such as time or space. You will examine the classes P and NP, and how to show problems are NP-complete. You will also consider other practically important classes such as: PSPACE, and its relevance to adversarial games, and NC, and its relevance to understanding of parallel computation and the limitations of its effectiveness. You will also consider classes BPP for probabilistic computation, and BQP for quantum computing, along with ideas of post-quantum cryptography based on NP-hard problems. You will look at the practical implications of computability and complexity in the context of real-world problems, such as vehicle routing, scheduling, timetabling, machine learning, and quantum computing.  

You’ll examine the principles of 3D computer graphics, focusing on modelling the 3D world on the computer, projecting onto 2D display and rendering 2D display to give it realism.

Through weekly lectures and laboratory sessions, you’ll explore various methods and requirements in 3D computer graphics, balancing efficiency and realism.

You’ll examine current techniques for the extraction of useful information about a physical situation from individual and sets of images.

You’ll cover a range of methods and applications, with particular emphasis being placed on the identification of objects, recovery of three-dimensional shape and motion, and the recognition of events.

You’ll learn how to implement some of these methods in the industry-standard programming environment MATLAB.

You’ll spend around three hours a week in lectures and laboratory sessions.

You’ll be given a basic introduction to the analysis and design of intelligent agents, software systems which perceive their environment and act in that environment in pursuit of their goals.

You’ll cover topics including:

• task environments
• reactive, deliberative and hybrid architectures for individual agents
• architectures and coordination mechanisms for multi-agent systems

You will spend around four hours each week in lectures and tutorials for this module.

Students taking part in activities relating to programming experience such as developing apps in their spare time, contributing to open source projects, or building things in hackathons may receive academic credit for showing they have experience and excellent development skills. The emphasis of this module is that you provide evidence of your significant extra-curricular software development experience. Students will only be able to register for this module with the approval of the convenor/school, once the material for assessment has been checked.

Data Visualisation is the process of extracting knowledge from complex data, and presenting it to users in a manner that is appropriate to their needs. This module provides the foundation for effective Data Visualisation design. You will learn about the different approaches to constructing visualisations, including the representation of ambiguous and time-series data. You will also learn about cognitive and visual perception theories that help explain how humans process information visually, and how to apply these to the design of effective visualisations. 

If you want to learn advanced design and implementation of interactive Data Visualisation, you should consider taking the linked module COMP3022 Data Visualisation Project, of which this module is a pre-requisite. Together, these two modules form an integrated 20 credit programme of study.

This module is an introduction to the design of human-AI interaction to ensure the AI-driven systems we build are beneficial and useful to people.

The module will cover practical design topics including methods and techniques such as natural language processing and human-robot interaction. The module will also consider societal and theoretical concerns of human-AI interaction, including the ethics of AI, responsible innovation, trust, accountability and explainable AI.

The practical component of the module will involve building AI-driven systems that drive conversational experiences, such as a text-based ‘chatbots’ and speech-controlled services/ ‘skills’, involving automatic speech recognition and natural language processing.

You’ll perform an individual project on a topic in computer science. You’ll produce a 15-25,000 word project report under the guidance of your supervisor, who you will meet with for an hour each week.

The topic can be any area of the subject which is of mutual interest to both the student and supervisor, but should involve a substantial software development component.

Students taking part in activities relating to industrial experience in a computer science or software engineering enterprise may obtain academic credit for them. A full list of approved activities is available from the School Office. Activities will be related to demonstration of involvement in development of complex software in a team situation, subject to quality control procedures of an industrial or business practice. Evidence of working to and completing tasks relating to targets set by an employer and directly related to software development/programming will be required. Students will have undertaken an agreed number of hours on the activities, identified personal goals and targets in relation to these activities and maintained a reflective portfolio as a record of evidence of their competence and achievements. The nature of the activities undertaken will be subject to the approval of the module convenor before acceptance on the module.

This module provides an opportunity to put into practice knowledge and understanding that you have developed through the linked module COMP3021. You will gain practical experience of how to design and evaluate a distinctive interactive visualisation which presents information gathered from a complex and interesting data source.  

Your project will be supported by seminars that introduce practical topics that are essential to effective visualisation design, and which have not been considered in COMP3021, including specific algorithms for extracting information from data, structured processes for designing visualisations and selected elements of design aesthetics (such as colour choice and typography). You will gain experience in web-based technologies that enable the implementation of multi-layered and interactive data visualisations.

Providing an introduction to machine learning, pattern recognition, and data mining techniques, this module will enable you to consider both systems which are able to develop their own rules from trial-and-error experience to solve problems as well as systems that find patterns in data without any supervision. 

You’ll cover a range of topics including:

• machine learning foundations
• pattern recognition foundations
• artificial neural networks
• deep learning
• applications of machine learning
• data mining techniques
• evaluating hypotheses

You’ll spend around six hours each week in lectures and computer classes for this module.

You’ll look at the development of software applications for mobile devices, with a practical focus on the Android operating system. You’ll consider and use the software development environments for currently available platforms and the typical hardware architecture of mobile devices. You’ll spend around three hours per week in lectures and computer classes.

This module focuses on some of the fundamental mathematical concepts that underlie modern programming and programming languages emphasizing the role of types. We will use a dependently typed programming language/interactive proof system (eg Agda) to implement some concepts on a computer.

Example topics include

• basic lambda calculus
• operational semantics
• domain theory
• types, propositions as types and formal verification.

You will engage in a mix of lectures and working in the lab with an interactive proof system.

This module introduces tools, techniques, and theory needed for programming real-world applications functionally, with a particular emphasis on the inherent benefits of functional programming and strong typing for reuse, maintenance, concurrency, distribution, and high availability. These are all aspects that have contributed to the popularity of functional programming for demanding applications eg in the finance industry and have also had a significant impact on the design of many modern programming languages such as Java, C#, and Rust, and frameworks such as MapReduce and React.

Topics typically include functional design patterns, pure data structures, reactive programming, concurrency, frameworks for web/cloud programming, property-based testing, and embedded domain-specific languages. The medium of instruction is mainly Haskell, but other functional languages, for example, Erlang, may be used where appropriate and for a broader perspective.

If you wish to study some particular topic in scope of this module in more depth, you are encouraged to consider taking the module Real-world Functional Programming Project.

Students taking part in approved activities, such as running code clubs in schools, organising school computing activity days, or becoming active STEM ambassadors, may receive academic credit for demonstrating they have actively contributed to the development of younger students. Students will have undertaken an agreed number of hours on the activities, identified personal goals and targets in relation to these activities and maintained a reflective portfolio as a record of evidence of their competence and achievements. Students will only be able to register for this module with the approval of the convenor/school, once the material for assessment has been discussed.

This module is part of the software engineering theme.

This module covers the following topics:

• management of the introduction of new software or IT systems
• software project management practices
• practical experience of use of an Agile software development project management process
• practical experience of use of Test Driven Development, pair programming and various approaches to software management tools, including the use of software versioning, project management planning tools and continuous integration and deployment

Through a two hour lecture each week, you’ll be introduced to concepts and techniques for software testing and will be given an insight into the use of artificial and computational intelligence for automated software testing. You’ll also review recent industry trends on software quality assurance and testing.