Computing - BSc (Hons)

This module provides an introduction to object-oriented software development. Software pervades many aspects of most professional fields and sciences, and an understanding of the development of software applications is useful as a basis for many disciplines. This module covers the development of simple software systems. Students will gain an understanding of the software development process, and learn to design and implement applications in a popular object-oriented programming language. Fundamentals of classes and objects are introduced and key features of class descriptions: constructors, methods and fields. Method implementation through assignment, selection control structures, iterative control structures and other statements is introduced. Collection objects are also covered and the availability of library classes as building blocks. Throughout the course, the quality of class design and the need for a professional approach to software development is emphasised and forms part of the assessment criteria.

Mathematical reasoning underpins many aspects of computer science and this module aims to provide the skills needed for other modules on the degree programme; we are not teaching mathematics for its own sake. Topics will include algebra, reasoning and proof, set theory, functions, statistics and computer arithmetic.

An introduction to databases and SQL, focussing on their use as a source for content for websites. Creating static content for websites using HTML(5) and controlling their appearance using CSS. Using PHP to integrate static and dynamic content for web sites. Securing dynamic websites. Using Javascript to improve interactivity and maintainability in web content.

This module aims to provide students with an understanding of the fundamental behaviour and components (hardware and software) of a typical computer system, and how they collaborate to manage resources and provide services in scales from small embedded devices up to the global internet. The module has two strands: 'Computer Architecture' and ‘Operating Systems and Networks’. Both strands contain material which is of general interest to computer users; quite apart from their academic value, they will be useful to anyone using any modern computer system.

This module provides an introduction to human-computer interaction. Fundamental aspects of human physiology and psychology are introduced and key features of interaction and common interaction styles delineated. A variety of analysis and design methods are introduced (e.g. GOMS. heuristic evaluation, user-centred and contextual design techniques). Throughout the course, the quality of design and the need for a professional, integrated and user-centred approach to interface development is emphasised. Rapid and low-fidelity prototyping feature as one aspect of this.

The module introduces students to data analysis and statistics techniques that are important in the application of computers to business and industry. This includes summarising data, using measures of central tendency and dispersion, and effective graphical representations. Various probability models, including normal and binomial distributions, sampling and inference and predictive techniques are introduced. Regression and time series analysis also covered, along with what-if analysis tools.

The module teaches students to program in software such as Matlab and/or create spreadsheets using VBA scripting. These tools are used to handle data, variables and arrays, to display output data using built-in functions and develop new functions. Various problem-solving techniques and plotting for data visualisation are introduced.

Design and communication, what makes for good written communication, how people get and process information, Personal Development Project, effective spoken communication, how to work successfully in a group, doing academic research, about preparing and giving a presentation, history of computing and the history of communication, the effects of technology, Health and safety issues with computing, the Business of Computing, Employment in IT, software development and software engineering, preparing for examinations, designing –for the web: web usability and web accessibility, the basics of IPR, relevant Laws applying to the use and development of computing, such as the Computer Misuse Act and the Data Protection Acts.

This module builds on the foundation of object-oriented design and implementation found in CO320 to provide both a broader and a deeper understanding of and facility with object-oriented program design and implementation. Reinforcement of foundational material is through its use in both understanding and working with a range of fundamental data structures and algorithms. More advanced features of object-orientation, such as interface inheritance, abstract classes, nested classes, functional abstractions and exceptions are covered. These allow an application-level view of design and implementation to be explored. Throughout the course, the quality of application design and the need for a professional approach to software development is emphasised.

This module provides an introduction to the theory and practice of database systems. It extends the study of information systems in Stage 1 by focusing on the design, implementation and use of database systems. Topics include database management systems architecture, data modelling and database design, query languages, recent developments and future prospects.

Building scaleable web sites using client-side and and server-side frameworks (e.g. JQuery, CodeIgniter). Data transfer technologies, e.g. XML and JSON. Building highly interactive web sites using e.g. AJAX. Web services. Deploying applications and services to the web: servers, infrastructure services, and traffic and performance analysis. Web and application development for mobile devices.

Packet data networks, overview of general equipment and function (e.g. hubs, switches, routers). Large network architecture (e.g. the Internet).

The OSI Seven layer model and packet encapsulation.

An understanding and appreciation for physical issues (such as cabling and wireless mediums, bandwidth, interference, etc).

Data-link layer issues (e.g. IEEE 802.3, IEEE 802.11, collisions, retransmissions, error recovery)

Network layer issues covering underlying protocols (e.g. IPv4/IPv6) and routing protocols (e.g. RIP/OSPF/AODV)

Transport layer issues and protocols (e.g. TCP/UDP)

Session layer issues and protocols (e.g. TCP).

Presentation layer overview

Application layer protocols (e.g. DNS, HTTP, FTP, SMTP/POP3)

The module studies in detail the activities and artefacts associated with software development process as performed by a development team (i.e. programming in the large).

Fundamentals: Pseudocode; Primitive and object types; Multi-dimensional arrays; Resizing arrays; Loops; conditionals and recursion

Data structures and algorithm design: Dynamic data structures, such as linked lists, trees, maps, heaps, bags, queues (priority queues) and stacks (LIFO/FIFO); Sorting and searching algorithms; Graphs and graph algorithms (depth, breadth-first search and shortest path).

The module studies in detail the activities and artefacts associated with the software development process as performed by a development team, particularly one that adopts an Agile methodology. Topics include

• Concepts, principles, practice and philosophy of an Agile approach to software development

• Collaboration: environment, programmer collaboration, team values, customer involvement, standards, reporting and professional responsibility

• Planning: release and iteration/sprint planning, risk assessment, stories and estimating

• Development: incremental requirements, customer tests, test-driven development, refactoring, simple design, incremental design and architecture, spike solutions,

performance optimisation

• Agile project management: roles, values and team philosophy; management of scope, time, cost, quality and risk.

• Broad concepts of software security for users as well as system developers, including secure online behaviour and computer security both in work and home

environments. Think about the risk of software security breaches for users.

• Systems Analysis.

• Object-Oriented methods and the use of UML for modelling of requirements (Class, Use Case, Activity, Sequence and State diagrams).

Students will apply Agile Development techniques to a prescribed problem that involves the development of a software solution.

Students undertake an individual project, which involves the specification and development of a software solution. Two members of academic staff will be involved in the supervision and monitoring of the project work. One member of academic staff will assume the role of client and the second that of mentor. Students will meet regularly with the client to review progress and validate development to-date. The mentor will support students to ensure the client's desired functionality is interpreted correctly and to encourage the adoption sound software engineering principles.

Towards the end of the project, each student will:

• Prepare a technical report that describes their solution strategy, the result of their project and reflections on what the student earned from the project;

• Present and give a demonstration of their software solution to the academic supervisors and other students.

Students taking this module will undertake two or (typically) more assignments for the Kent IT Clinic (KITC). Each assignment will be of one of three types:

Work on one of KITC's contracts with an external client. To the extent that client-funded work allows, every student will be given at least one assignment of this type. Wherever practical, a student will be encouraged to participate in the negotiation and pricing of contracts, under the ultimate supervision of KITC management. For each assignment, the student may work on the assignment individually or as part of a group, as directed by KITC.

A contribution to the infrastructure of KITC itself. These assignments work in a similar way to external assignments, but with KITC as the client.

Formulating a costed proposal for the future development of KITC, and presenting reasoned argument in support of the proposal to KITC management, as a candidate for inclusion in KITC's strategic plan for the following academic year. Every student will have at least one assignment of this type.

Security has always been an important aspect of computing systems but its importance has increased greatly in recent years. In this module you learn about areas where security is of major importance and the techniques used to secure them. The areas you look at include computer operating systems (and increasingly, distributed operating systems), distributed applications (such as electronic commerce over the Internet) and embedded systems (ranging from smart cards and pay-TV to large industrial plant and telecommunications systems).

E-commerce is an increasingly important area for consumers, businesses and national economies. This module introduces what is meant by electronic commerce, and discusses its economic and social implications, its drivers and limitations. You will learn about the principal features of business-to-business and business-to-customer e-commerce and compare them with traditional forms of trading. The course also includes the chance to implement a simple end-to-end e-commerce system.

Indicative topics include:

• Resource Description Framework (RDF) & RDF Schema:

• Information representation and knowledge exchange on the web

o Applications of RDF

• RDF Query and Inference Languages (e.g. SPARQL etc.)

• Web Ontology Language (OWL):

o Publishing and sharing of ontologies

• Knowledge management, asset management, enterprise integration

o Automated agents

• Existing Shared Ontologies (e.g. FOAF, DC, SKOS etc.)

• Metadata and Provenance

• The Wider Picture:

o Data trust and proof issues

o Computer law and professional issues

• The future of the Web (these lists are not exhaustive):

o Web 3.0: the Semantic Web; cognitive architecture; automated reasoning; distributed computing; composite applications; semantic wikis etc.

• Aim to give students the tools to critically evaluate the Semantic Web (and alternative proposals)

Students taking this module will undertake one or (typically) more assignments for the Kent IT Clinic (KITC). Each assignment will be of one of three types:

Work on one of KITC's contracts with an external client. To the extent that client-funded work allows, every student will be given at least one assignment of this type. Wherever practical, a student will be encouraged to participate in the negotiation and pricing of contracts, under the ultimate supervision of KITC management. For each assignment, the student may work on the assignment individually or as part of a group, as directed by KITC. A contribution to the infrastructure of KITC itself.

A contribution to the infrastructure of KITC itself. These assignments work in a similar way to external assignments, but with KITC as the client.

Formulating a costed proposal for the future development of KITC, and presenting reasoned argument in support of the proposal to KITC management, as a candidate for inclusion in KITC's strategic plan for the following academic year.

Data mining is a process of extracting, from a large amount of data, interesting patterns that are non-trivial, hidden, new and potentially useful. It is a rapidly growing field and is becoming important because with the increasing quantity and variety of online data collections by many organizations and commercial enterprises, there is a high potential value of patterns discovered in those collections.

This module looks at different data mining techniques and gives you the chance to use a state-of-the-art data-mining tool and evaluate the quality of the discovered knowledge. The topics include: introduction to data mining and knowledge discovery process, data description, , data pre-processing, attribute selection, market basket analysis and association rules, classification, clustering, outlier detection, post-processing, social impact and trend of data mining.

This module aims to enable students to understand the social and economic changes that have raised the status of enterprise, small business and entrepreneurial ventures in the global economy. It examines the diverse nature of entrepreneurs, their characteristics and motivations, as well as the barriers and issues facing entrepreneurs when planning and establishing a new venture.

The key topics of the module are:

1) Factors that have influenced the growth of the enterprise culture in the UK.

2) The role and relevance of SMEs in the UK economy; definitions of SMEs; statistical information; Government policies and initiatives, and support agencies.

3) Whether entrepreneurs are born or made; whether enterprise skills can be taught or learned, and whether entrepreneurs differ from business owners and other managers.

4) Enterprise and innovation development in organisations.

5) Differences in attitudes, objectives, skill requirements and business strategies between small and large firms.

6) Surviving the early stages of business development, including failure rates in new and small enterprises and barriers to growth and development.

7) The planning process for starting a new venture – including risks and liabilities; problems and pitfalls, and potential profit and success.

8) The protection of ideas and intellectual capital.

9) Funding a new enterprise, including via 'friends, family and fools', business angels and venture capitalists.

10) Enterprise in different contexts, including corporate enterprise, public sector enterprise and social enterprise.

The understanding and application of enterprise knowledge is seen as a transferable skill that can have cross-school application within the University, in that it has relevance to students from a broad range of academic disciplines who might be considering self-employment after graduation.

The curriculum is based on the Small Firms Enterprise Development Initiative (National Standards-setting body for small business) Standards for Business Start-up, but has been expanded to include contemporary issues such as Intellectual Property and recent legislation.

The module will include the following areas of study:

1) Why firms become insolvent – economic financial and operational reasons for business failure; risks & liabilities; skills requirements for business ownership; self-development planning; sources of advice, and support for businesses.

2) The new business planning process and format - developing and evaluating the business idea, and producing a business plan for potential lenders.

3) Financial aspects – budgetary planning and control; cash-flow and working capital; understanding financial accounting and key financial documents; break-even analysis; credit control, and debt recovery.

4) Market research, competition and barriers to market entry - identifying customers; market segmentation; planning the sales and marketing processes; customer perceptions and customer care, and developing quality standards for the business

5) Legal issues - reporting requirements; UK & EU law relevant to small businesses; business formats and trading status and their respective risks and liabilities; insurance; insolvency, and intellectual property rights such as patents and copyright.

6) Planning and employing staff - planning and obtaining premises; physical and financial resources, and the phased implementation of the business plan.

The following is indicative of topics/themes this module will include:

• An overview of basic concepts related to Computational Intelligence (CI) techniques, such as heuristic search and optimisation

• Presentation of different CI algorithms, such as hill climbing, simulated annealing, genetic algorithms and genetic programming

• An overview of basic concepts related to real-world problems related to business, economics and finance, such as financial forecasting, automated bargaining, portfolio optimisation, and timetabling

• The use of Computational Intelligence techniques to solve real-world problems

• Computational Intelligence decision support systems and software wind tunnels for testing new markets and strategies

An overview of basic concepts related to eHealth and a perspective on current HIT (Health Information Technology) and innovation. Review of current healthcare related IT systems. The use of information technology for handling clinical data, health systems. Data representation and knowledge management. Security and privacy. Ethics and legal requirements of eHealth systems. Clinical decision support systems. TeleHealth tools for remote diagnosis, monitoring, and disease management. Delivery and monitoring platforms for both hospitals and home environment. Innovation in eHealth systems leading to start-up companies.