Computer Science (Software Engineering)

Core Modules

Year 1

• Object Oriented Programming I

  This module teaches programming and object-orientation concepts. Students will learn about program basics (variables, types, scope, lifetimes), control flow (if-constructs, for-loops, while-loops), data structures (strings, sets, lists, trees), objects (classes and inheritance), exceptions (throwing and catching) and file I/O (streams, file reading and writing).

• Object Oriented Programming II

  This module teaches programming and object-orientation concepts, (building on what is taught in Object Oriented Programming I). Students will reinforce their knowledge about program basics (eg variables, types, scope, lifetimes), algorithms (e.g. recursion, searching, sorting), data structures (eg sets, lists, trees), objects (eg classes, dynamic dispatch, interface, inheritance, generics), exceptions and I/O (eg streams, file reading, writing and copying). Furthermore, the course also teaches fundamentals of coding best practices.

• Programming laboratory

  In this module you will develop an understanding of the building of computer systems and applying  your knowledge as patrt of a small team to construct a fully-fledged software product. 

• Internet Services

  In this module you will develop an understanding of how the internet works and its key protocols. You will look at the technologies used for web development, including scripting languages and their potential for adding dynamic content to web sites and applications. You will consider the role of web services and related technologies, and will examine the fundamental principles of network security.

• Mathematical Structures

  In this module you will develop an understanding of the formal reasoning for sets, relations, functions and cardinality. You will look at the structures for program data and representation and learn to write and reason recursive definitions and prove results by induction and contradiction. You will also consider the representation and reasoning of problems using graphs.

• Machine Fundamentals

  In this module you will develop an understanding of the handling of large and infinite objects within a programming environment. You will learn how to use formal logic to design, reason about and minimise switching circuits, and write basic programs in assembly language. You will consider the binary representations of signed and unsigned integers and how to write regular expressions to describe sets and build deterministic automata to recognise these. You will also examine the use of automata machines in the design and reasoning of sequential flow systems.

• Mathematical Methods for Computer Science

  This module provides the necessary Mathematics to prepare you for topics such as Machine Learning and Information Security which have become essential to the discipline. In particular, this will include an introduction to Linear Algebra (taught in a way relevant to Computer Scientists), Probability and Statistics.

• Software Design

  In this module you will develop an understanding of software design and engineering processes, including the Waterfall and Agile methodologies. You will learn how to identify common software requirements and see how these have been considered in existing systems. You will look the techniques of software design and how software engineers communicate their design ideas. You will consider the importance of documentation and the usage of current industry-standard notations such as user stories and the unified modeling language (UML). You will also analyse and critique the design of existing software looking at the user experience as a measure of its fitness for purpose.

• Academic Integrity

  This module will describe the key principles of academic integrity, focusing on university assignments. Plagiarism, collusion and commissioning will be described as activities that undermine academic integrity, and the possible consequences of engaging in such activities will be described. Activities, with feedback, will provide you with opportunities to reflect and develop your understanding of academic integrity principles.

   

Year 2

• Software Engineering

  In this module you will develop an understanding of software engineering techniques and the managerial discipline required to work as part of a team. You will look at basic object-oriented concepts and consider the need for effective program documentation, testing, readability, and modifiability. You will consider the tools used to support software development, such as version controllers, debuggers, and code style checkers, and see how these are integrated into an industry-standard development environment (IDE). You will deliver a small-scale project using test-driven development.

• Small Enterprise Team Project

  This module aims to assist students in appreciating the role of the computer professional through the practical experience of developing medium scale software as part of a team. You’ll study: The software lifecycle, including: software development, planning and documentation. Team development, communication, managing risks and conflicts. Practical experience of standard industrial software engineering. Agile project management, use of version control in a team, IDEs, etc. A medium scale agile software development project, conducted by teams of students. Meetings with an external customer to determine the requirements for a product.

• Operating Systems

  In this module you will develop an understanding of the function and architecture of network operating systems. You will look at the role of an operating system, considering processes, memory and file systems. You will learn to write basic shell scripts, see how services are used at the operating system-level, and evaluate the theory and practice of existing operating systems. You will also examine the UNIX shell, including starting programs, input and output streams, pipes, filters, and utilities.

• Databases

  In this module you will develop an understanding of the basic concepts of database technology, including the need for database integrity and robustness, and the use of a modern database system in a web-based environment. You will look at database design and the theory of the relational view of data, learn to describe the crucial issues concerning database integrity and recovery from failure, and write search query language (SQL) queries. You will also consider the process of designing and implementing a database, from the user specifications to the final design, and implement an interface to an SQL database using an application programming interface (API).

• Algorithms and Complexity

  In this module you will develop an understanding of the design of algorithms, with a focus on time and space complexity. You will examine basic algorithms, looking at the implementation and analysis of linear search, binary search, and basic sorting, including insertion sort, selection sort, merger sort, quick sort, and heap sort. You will consider alternative data structure representations, such as binary search trees, hash tables, and binary heaps, and will gain an insight into the basics of graph algorithms.

• Introduction to Information Security

  In this module you will develop an understanding of how information security may be influenced by real-world design and implementation decisions. You will look at the different cryptographic algorithms, considering their use, advantages and disadvantages. You will use these cryptographic primitives to review and evaluate cryptographic protocols, and examine the rational decisions in the design of tokens and secure elements.

• Computer and Network Security

  In this module you will develop an understanding of computer and network security. You will look at software vulnerabilities, hands-on hacking-oriented attacks, memory errors, and web and network security. You will learn how to identify such vulnerabilities and consider the countermeasures that can mitigate their exploitation. You will also examine malicious software (malware) as a typical consequence of a successful software exploitation.

Year 3

• Individual Project

  This module provides the opportunity to demonstrate independence and originality, to plan and organise a large project over a long period, and to put into practice the techniques taught throughout the degree course.

• User-Centred Design

  This module introduces user-centred design aspects and challenges in interactive traditional, augmented and virtual reality contexts, and addresses the approaches that can be used to create displays and interfaces to enhance user experience.

Year 4

• MSci Team Project

  The main aim of the Team Project is to give extensive experience to students in working in projects for real clients, as part of a team and operating as a company. Teams of students will: work in the context of a company where they have specific responsibilities; engage with real clients and determine their requirements for a significant piece of software; devise, estimate, design, implement, test, document and critically evaluate software; present their work and communicate their findings to the client.

Optional Modules

Below is a taster of some of the exciting optional modules that students on the course could choose from during this academic year. Please be aware these do change over time, and optional modules may be withdrawn or new ones added.

Year 1

• All modules are core

Year 2

• Symbolic Artificial Intelligence

  The aim of this course is to introduce students to the basic principles, methods and techniques of the symbolic AI approach, where one develops an intelligent system using rules, knowledge and actions that are interpretable. The intention is to provide the foundations of the key principles of symbolic AI, so that these can be combined with non-symbolic AI courses in the area. The course will start by providing an overview of the approaches in the field by referring to the wider historical context in which the AI vision was set and will further motivate the content to be taught by presenting existing and potential applications. After the overview, the course will deliver a series of topics from first principles, including the role of first-order logic for knowledge representation, computational reasoning and problem solving systems, the use of search as a capability for exploring alternative solutions, and how AI systems use symbolic knowledge to plan and learn from first principles.

• Multi-dimensional Data Processing

Year 3

• Computational Finance
• Machine Learning

  In this module you will develop an understanding of key methods and techniques in machine learning. You will study approaches such as nearest neighbours, ridge regression, Lasso, and support vector machines for both classification and regression tasks. You will explore the use of different distance measures and the kernel trick, as well as practical kernels and their applications. The module also introduces conformal prediction and its application to various algorithms. You will gain experience in implementing basic machine learning algorithms and develop an awareness of how these methods can be applied in fields such as industry and medicine.

• Applications of Cryptography

  In this module you will develop an understanding of the fundamentals behind cryptography and how it is deployed in real systems. You will look at a range of security services that can be provided by cryptography and the mechanisms behind them, such as symmetric and public-key encryption, hash functions, MACs, digital signatures and authentication protocols. You will consider the architecture of security systems using cryptography, including key management, implementation issues, cryptographic standards and crypto politics, and examine real-world applications such as 3G, EMV, and SSL/TLS.

• Critical Infrastructure Security

  The module covers key areas of cyber security with the critical national (information) infrastructure forming its background. Fault and attack models for information systems and cyber-physical systems are covered in the form of multiple techniques including variants of attack trees allowing probabilistic attack and defence refinements. The module covers models of large-scale networks and their robustness properties to both random failures and particularly to deliberate attacks and discusses how key elements of the CNI such as the Internet but also other infrastructure sectors such as power and transport sectors can be captured by such models. The security of cyber-physical systems and particularly industrial control systems is another major component of the module, including case studies of attacks by state actors and analyses of control system protocols as well as properties peculiar to CPS.

• Digital Forensics
• Smart Cards, RFIDs and Embedded Systems Security
• IT Project Management
• Software Language Engineering
• Compilers and Code Generation
• Computational Optimisation
• Functional Programming and Applications
• Deep Learning
• Security Management
• Software Verification

  This module introduces students to system verification using model-checking techniques that are now adopted in industry. Model checking is a formal technique that, over the last two decades or so, has proved to be a very attractive approach towards verifying the correctness of computer-based control systems. It allows for desired behavioral properties of a given system to be verified on the basis of a suitable model of the system through systematic inspection of all states of the model. Elements of language theory and automata Formal modelling of concurrent systems and logical requirement specifications Temporal logic (linear and branching) (Symbolic) model checking Introduction to the SPIN and SMV model checkers.

• Advanced Algorithms & Complexity

  This course samples topics from various aspects of algorithms construction and analysis, including Graphs, graph algorithms, and applications, e.g., directed and undirected graphs; directed acyclic graphs and acyclic orderings; and connectivity in directed graphs; Algorithm design paradigms: General methods for designing and analysing efficient algorithms, such as dynamic programming, a more careful treatment of the divide and conquer method, and general strategies such as backtracking search or greedy approaches; Further application areas, such as string algorithms, network flows, and logic problems; Complexity and lower bounds: NP-hardness and NP-completeness; problem reductions; conjectural lower bounds, and lower bounds against problems in P; and methods for dealing with NP-complete problems, including heuristic approaches, exact algorithms, and tractable special cases.

Year 4

• Data Analysis
• Online Machine Learning
• Data Visualisation and Exploratory Analysis
• Advanced Distributed Systems
• Large Scale Data Storage and Processing
• Critical Infrastructure Security

  The module covers key areas of cyber security with the critical national (information) infrastructure forming its background. Fault and attack models for information systems and cyber-physical systems are covered in the form of multiple techniques including variants of attack trees allowing probabilistic attack and defence refinements. The module covers models of large-scale networks and their robustness properties to both random failures and particularly to deliberate attacks and discusses how key elements of the CNI such as the Internet but also other infrastructure sectors such as power and transport sectors can be captured by such models. The security of cyber-physical systems and particularly industrial control systems is another major component of the module, including case studies of attacks by state actors and analyses of control system protocols as well as properties peculiar to CPS.

• Digital Forensics
• Secure Business Architectures
• Security Management
• Security Testing Theory and Practice
• Smart Cards, RFIDs and Embedded Systems Security
• Computational Optimisation
• Business Intelligence Systems, Infrastructures and Technologies
• Autonomous Intelligent Systems

  This specialist module focuses on acquiring a deep understanding of the principles and techniques that are needed to design and build autonomous intelligent systems (AISs). The module will start with an introduction to AISs and real-world examples of them. It will then cover knowledge representation and engineering techniques based on formal logic. The module will then tackle autonomous decision making techniques, from AI planning to probabilistic reasoning and Markov Decision Processes. Reinforcement learning and techniques for cooperation and coordination between artificial agents will also be taught. All these topics will be discussed both from a theoretical point of view, during the lectures, and from a practical point of view, during the labs.