Advanced Software Engineering

Module code: 7CCSMASE
Credit level: 7
Credit value: 15
Semester:  Semester 1 (autumn) 

Aims
To convey an understanding of the basic elements of software measurement and testing, in particular focusing on automated test data generation and with a discussion of the relative strengths and weakness of each technique.

Learning Outcomes
To be able to describe, apply and critique several well-known software metrics. To be able to describe and apply several well-known software testing techniques. To be able to compare testing techniques and present arguments relating to the most appropriate choice thereof.

Provisional Syllabus
Measurement: Representation and modelling, Scales, Structural Measures
Unit testing: Control Flowgraph Based testing including Data Flow based testing
Finding test cases using test data generation techniques. Coverage
Slicing and static analysis techniques
Industrial applications and industrial relevance of testing
Comparative software testing techniques

Module code: 7CCSMGPR
Credit level: 7

To provide the experience of working in a syndicate to design, implement and document a substantial software product.

Module code: 7CCSMDAS
Credit level: 7
Credit value: 15
Semester:  Semester 2 (spring) 

Aims
To explore the practice of software architecting as applied to the development of enterprise systems. To learn about software architecture, architecture patterns, frameworks, design patterns, pattern languages, layers of change, the architecting process and the practical process of software design and implementation. Ideas are put into practical perspective through an introduction to the UML2 superstructure, enterprise component middleware.

Learning Outcomes
To be able to function as a software architect; to have an advanced knowledge of the issues, techniques and processes involved in architecture design; ability to design .NET-based enterprise software systems; expert proficiency in the UML2 superstructure to design architectures; to be able to work with and design metamodels and model transformations.

Provisional Syllabus
Components and connectors in the UML2 superstructure Architectural styles Domain-specific metamodels and case studies A metamodel for enterprise components
Semantics through the OCL
Metamodelling with the Meta Object Facility Model driven engineering and model-driven architecture

Module code: 7CCSMAPP
Credit level: 7

To provide specialist knowledge and understanding of the core aspects of policy representation in the context of Computer Science, including an understanding of access control and privacy policy formulation and implementation for centralised and decentralised computer systems.

Module code: 7CCSMART
Credit level: 7
Credit value: 15
Semester:  Full-year 
Assessment:  coursework 

Aims
To teach you to read and understand research papers and research lectures on your own, and pursue a research topic.

Learning Outcomes
You should obtain a good understanding of a particular technical area at a level that goes substantially beyond the taughts MSc materia.  You should also learn to explore a research area, to identify the important issues and understand their connection with each other and to demonstrate your technical understanding by presenting the results to a scientifica audience.

Provisional Syllabus
In this optional module, you will study advance research literature preferably in an area that is related to the material taught in your programme.

7CCSMART is a first-term module, with work starting at the beginning of the first term, but with the assignment continuing into the second term. Lectures will cover research methods, report/paper writing, and presentation techniques. You must attend at least five selected research seminars during the first term and read several related research papers.

You must agree your choice of research topic with the module organiser, which must be on a topic of in the research area of one of the members of the Department. Towards the end of the first term, you must submit a first draft of a report (approximately 10-15 pages), which will be reviewed by the organiser and other students. The final draft of the report must be submitted in the second term. The submitted report forms the basis of the assessment.

Topics will include:
Doing Research
Writing
Writing Scientific Papers
Presenting Scientific Papers
References
Sources
Refereeing

Module code: 7CCSMAMS
Credit level: 7
Credit value: 15
Semester:  Semester 1 (autumn) 

Aims
To describe some techniques employed in the characterisation of agents and multi-agent systems. To provide a critical introduction to theories and methods regarding multi-agent computer systems and their component agents.

Learning Outcomes
On completion of the module, you will be expected to have acquired: A thorough, systematic understanding of key features of current theories and methods regarding multi-agent systems and their component agents; A sound appreciation of the conceptual issues involved in the characterisation of agents and their abilities; Knowledge of some of the main techniques employed in the formal characterisation of agents and multi-agent systems; An ability to critically evaluate current work in this field, and to evaluate the principal theories and methods.

Provisional Syllabus
Topics will be selected from:
Intelligent agents and their design
Knowledge in multi-agent systems
The Belief-Desire-Intention model of rational agents
Reactive and hybrid agent architectures
Agent Communication: KQML, FIPA
Auctions and Negotiations Game Theory Argumentation based Reasoning and Communication
Agent-based methodologies Applications

Module code: 7CCSMCOM
Credit level: 7
Credit value: 15
Semester:  Semester 2 (spring) 

Aims
The aim of this module is to define, analyse and compare abstract models of computation and their associated programming paradigms.

Learning Outcomes
On successfully completing the module you should be able to demonstrate a deep knowledge and understanding of the fundamentals of formal languages and the principal models of computation and be able to work with theoretical/research-based knowledge at the forefront of the subject; judiciously apply and combine tools and techniques (frequently in novel ways) to solve a range of complex subject-specific problems with minimal direction; analyse subject material, draw inferences, and find relationships that demand that innovative thinking be engaged in and creativity be exhibited in formulating solutions; critically evaluate, exercise judgement, and compare and contrast relevant material with minimal guidance and to consider and argue for alternative, novel approaches; demonstrate a high degree of independence in managing your own learning and reflecting upon it in order to complete research tasks autonomously.

Provisional Syllabus
Introduction to abstract models of computation
Finite Automata, Push-Down Automata and applications to parsing
Turing machines
Functional calculi
Interaction-based systems
Concurrent computation

Module code: 7CCSMDSI
Credit level: 7

The aims of this course are to present properties, implementations, and applications of fundamental and advanced data structures required for the efficient representation, organisation, searching, and manipulation of computer data. The course uses the C++ programming language as the implementation environment.

Module code: 7CCSMDBT
Credit level: 7

To study present and predicted developments in database technology from a formal perspective.

Module code: 7CCSMDSM
Credit level: 7

This course aims to provide an overall understanding of the basic concepts and practical technology of distributed computing, an in-depth understanding of the considerations applied in designing software for distributed systems. It will give students knowledge of algorithmic and architectural techniques used to address these considerations, and provide means of assessing how well novel technologies are able to handle faults in distributed systems.

Module code: 7CCSMPDA
Credit level: 7
Credit value: 15
Semester:  Semester 1 (autumn) 

Aims
To provide you with an introduction and overview to the computational aspects of parallel and distributed computing. To introduce several important parallel computing models that capture the essence of existing and proposed types of synchronous and asynchronous parallel computers. To study typical models for distributed computing. To study a few typical algorithms for each model, selected from various basic areas such as sorting, selection, graphs, matrices, numerical problems, and computational geometry. To provide an important skill for those who may work with large applications since these usually must be implemented on a parallel or distributed system, due to their memory space and speed requirements.

Learning Outcomes
On successfully completing this module you should understand a number of different models of parallel and distributed computing and understand the basic techniques for designing algorithms in these models.

Provisional Syllabus
PART I: Parallel Models and Algorithms
Models of Parallel Computation:
PRAMs; Scan Vector Model; Complexity measures
Designing Parallel Algorithms:
Basic PRAM techniques; Doubling technique; Summation trees and prefix summation
Interconnection networks:
Graph models of networks; Network properties; Searching and sorting on meshes
Sorting and Searching on PRAMs:
Merge sort; Compare-exchange sorts; Batcher‟s sorting algorithms; Computing the Median
Pointer-based algorithms:
List ranking; Tree contraction; Connected components; Minimum spanning tree; All-pairs shortest path
Geometric Algorithms:
Convex hulls; Closest pair of points; Visibility
PART II: Distributed Models and Algorithms
Concepts of distributed computation:
Termination; Failure tolerance; Network topology
Distributed Search:
Distributed BFS
Random walks; Introduction to Markov processes; Random walks (hitting time, cover time (s.t)-connectivity
Distributed networks:
Broadcasting; Robust distributed networks

Module code: 7CCSMSIA
Credit level: 7
Credit value: 15
Semester:  Semester 2 (spring) 

Aims
This module will cover different approaches for building internet applications and the choice of design techniques and technologies involved from a software engineering perspective, considering issues of efficiency, modularity and maintainability.

Learning Outcomes
You will gain the ability to design and implement internet-based applications in a modular manner, using appropriate languages and techniques. You will also gain the ability to specify and design medium-sized enterprise information systems using appropriate languages and techniques.

Provisional Syllabus
Model-driven architecture and application to internet applications
Client-side processing techniques: JavaScript, HTML
Server-side processing techniques: JSP, Servlets, database interfaces, sessions, connection pools
Modularity and maintainability of internet applications
Java EE architecture and patterns
Web services

Module code: 7CCSMINT
Credit level: 7
Credit value: 15
Semester:  Semester 1 (autumn) 

Aims
To provide an overall understanding of the communication model used on the Internet. To provide an in-depth understanding of the main underlying software components of the Internet. To provide an overview of the main languages used on the Internet. To provide an understanding of security threats to Internet application and the main technologies used to tackle them. To give you an understanding of the motivations behind internet technologies, suitable for you to evaluate current and future options.

Learning Outcomes
On successfully completing this module you will:
Development of Knowledge and Understanding
Have a comprehensive and detailed knowledge of the computational model underlying the Internet and recent developments in this area.
Know some of the languages used to display, represent, and manipulate information on the Internet.
Understand the security mechanisms used to protect Internet applications from unauthorised use.
Understand how protocols and languages combine to solve communication problems.
Be aware of the issues concerning privacy of personal information on the internet, and be able to apply techniques to protect privacy in any Internet applications you develop.
Cognitive/Intellectual Skills
Be able to analyse Internet-related problems using appropriate techniques and evaluating alternatives.
Be able to design solutions to such problems and evaluate the success of those solutions, possibly developing novel approaches.
Apply your knowledge of the Internet and its languages to these solutions.
Key/transferable skills
Know how to access and evaluate different sources of information regarding Internet standards, and technology standards more generally.
Have experience of solving technical, Internet-related, problems, and arguing for solutions to them.
Practical Skills
Be able to apply your knowledge of languages to meet appropriate software requirements.

Provisional Syllabus
Introduction to the Internet
Historical perspective and current context
Architecture of the Internet
Internet infrastructure
Addressing models
Web servers
Communication model
Internet reference model
TCP/IP
IPv4 and IPv6
Connection handling and flow control
HTTP and other application layer protocols
Resource location
Web languages fundamentals
HTML/XHTML
Form handling
XML
XML validation with schemas
Web service languages
Security on the Internet
Authentication methods
Digital certificates
Public and private key encryption
SSL
Introduction to Web models of information
Semantic Web
Grid computing