University home » University Calendar » Courses » Faculty of Science » Computer Science

Computer Science

Stage I

Principles of Programming

An introduction to computers and computer programming in a high-level language. The role of computers and computer professionals in society is also introduced. The course is intended for students who may wish to advance in Computer Science or in Information Systems and Operations Management.

Principles of Computer Science

Extends the programming skills of COMPSCI 101, covering more advanced data structures and their representation and manipulation. Topics include: pointers, dynamic data structures (lists, queues, stacks, trees, hashtables), recursion, sorting and searching.

Prerequisite: COMPSCI 101

Mastering Cyberspace: An Introduction to Practical Computing

A practical introduction to computing. Topics include: web design, an overview of computer hardware and operating systems, effective use of common applications, using the Internet as a communication medium, applying programming concepts, and social implications of technology.

Stage II

Computer Systems 1

The low level representation of data and algorithms in the computer. An introduction to computer organisation. The instruction execution model. Assembly language programming. Study of a high-level language and how it is implemented at the machine level. Assembly and disassembly of instructions.

Prerequisite: COMPSCI 101 and 105

Computer Systems 2

Interacting with the operating system via a command line interface and use of a scripting language. Hardware support necessary to implement a secure multi-user operating system: user/kernel mode, exceptions and interrupts, virtual memory, context switching, synchronisation, interrupt driven input/output. An introduction to data communications: the OSI reference model, particularly how the lower layers combine to implement sockets.
Recommended preparation: Prior or concurrent enrolment in COMPSCI 210

Prerequisite: COMPSCI 101, 105

Algorithms and Data Structures

An introduction to the analysis of algorithms and data structures. Common abstract data types and their implementations. Asymptotic complexity analysis. Sorting and searching algorithms. Depth-first and breadth-first search and applications. Graph optimisation problems.

Prerequisite: COMPSCI 101, 105, and 15 points from MATHS 108, 150, 153

Discrete Structures in Mathematics and Computer Science

An introduction to logic, principles of counting, mathematical induction, recursion, relations and functions, graphs and trees, and algorithms. This course is suited to students who are interested in the foundations of computer science, mathematics and logic.

Prerequisites: 15 points from MATHS 108, 150, 153, COMPSCI 101, PHIL 101

Restriction: MATHS 255

Software Construction

Students will develop a software application of reasonable complexity through the application of established software development techniques. In doing so, students will demonstrate fundamental skills in object-oriented software development, GUI programming and application-level multithreading. In addition, students will learn established techniques to ensure that their software satisfies quality criteria.

Prerequisite: COMPSCI 101, 105

Enterprise Software Development

Develop a distributed application using an Enterprise technology. Demonstrate skills in data modelling, manipulating and querying; and accessing a remote database server. Model system requirements and design using established notations, to leverage a component-based Enterprise technology, and to use tools to support their activities. Collaborative work experience through pair programming.

Prerequisite: COMPSCI 101 and 105

Restriction: INFOSYS 280

Stage III

Computer Organisation

Modern processor architectures. Principles of modern processor design; pipelining; memory hierarchies; I/O and network interfacing; compiler and OS support; embedded processors; performance; multiprocessing.

Prerequisite: COMPSCI 210, 215 (PHYSICS 140 or 243)

Restriction: SOFTENG 363, COMPSYS 304

Modern Data Communications

The structure of data communications and networks, including the Internet, covering all levels of the communications architecture. The layered protocol model, data transmission and coding, link-level and local area network protocols, wide-area internetworking, routing, transport and security protocols. Basic application protocols as the foundation for distributed computing.

Prerequisite: COMPSCI 210 and (COMPSCI 215 or INFOSYS 224)

Restriction: SOFTENG 364

Applied Algorithmics

Fundamental design techniques used for efficient algorithmic problem-solving and software development. Methods that yield algorithms that are both provably correct and efficient. Efficiency of algorithms to provide a basis for deciding which algorithm is best for the job. Limits on the power of computers and the theory of NP-completeness. An introduction to methods whose correctness or performance is not guaranteed.

Prerequisite: COMPSCI 220, 225

Distributed Objects, Services, and Programming

Programming introduction to distributed services and to browser based applications. Introduction to functional programming for data integration. Specific topics will include simple distributed applications, using message-based, declarative or functional programming methods. Concepts of programming with XML, SOAP and HTTP based mechanisms, and programming for dynamic web content generation.

Prerequisite: COMPSCI 230 and 15 points at Stage II in Computer Science

Operating Systems

Operating system principles. Multi-user systems. Virtualisation. Scheduling. Concurrent processes, threads, synchronisation and deadlock. Memory allocation and virtual memory. Managing files, disks and other peripherals. Security, protection and archiving. Distributed systems and algorithms, location, migration and replication transparency. Real-time requirements. History of operating systems.

Prerequisite: COMPSCI 215, 230

Restriction: SOFTENG 370

Human-computer Interaction

Human behaviour and humans' expectations of computers. Computer interfaces and the interaction between humans and computers. The significance of the user interface, interface design and user centred design process in software development. Interface usability evaluation methodologies and practice. Includes a group development and evaluation project using current implementation techniques and tools.

Prerequisite: COMPSCI 230 or SOFTENG 206

Restriction: COMPSCI 370, SOFTENG 350

Mathematical Foundations of Computer Science

The aim of this course is to present mathematical models for programming languages and computation, and derive some theorems regarding what can and cannot be computed. Abstract programming languages (finite automata, context-free grammars, Turing and register machines) are studied. Basic concepts for programming languages, limits on computational power and algorithmic complexity are presented. Church-Turing thesis and quantum computing are briefly and critically discussed.

Prerequisite: COMPSCI 225 and (COMPSCI 220 or PHIL 222)

Fundamentals of Database Systems

Database principles. Relational model, Relational Algebra, Relational Calculus, SQL, SQL and Programming Languages, Entity Relationship Model, Normalisation, Query Processing and Query Optimisation, ACID Transactions, Transaction Isolation Levels, Database Recovery, Database Security, Databases and XML.

Prerequisite: COMPSCI 220, 225

Restriction: SOFTENG 351

Artificial Intelligence

The cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning.

Prerequisite: COMPSCI 220, 225

Restriction: COMPSCI 365, 366

Computational Science

Principles of computational science. Computational science is the development and application of computer algorithms and software to solve scientific and engineering problems including probabilistic computer modeling, computer-based statistical inference and computer simulation. Focus is on the analysis of real-world data with emphasis on Computational Biology and Computational Engineering.

Prerequisite: COMPSCI 220 and 15 points from STATS 101-125

Computer Graphics and Image Processing

Basic geometric processes including transformations; viewing and projection; back projection and ray tracing. Graphics modeling concepts: primitives, surfaces, and scene graphs, lighting and shading, texture mapping, and curve and surface design. Graphics and image processing fundamentals: image definition and representation, perception and colour models, grey level and colour enhancement, neighbourhood operations and filtering. Use of the OpenGL graphics pipeline.

Prerequisite: COMPSCI 210, 230

Restriction: COMPSCI 372, 375

Undergraduate Project in Computer Science

Each student taking one of these courses will be expected to do an individual practical project under the supervision of a member of staff. Only students with excellent academic records will be allowed to take these courses, and only after a supervisor and topic have been agreed upon by the Head of Department.

Prerequisite: Approval of Head of Department

Restriction: COMPSCI 690

To complete this course students must enrol in COMPSCI 380 A and B, or COMPSCI 380

Special Topic in Computer Science 1

Special Topic in Computer Science 2

Special Topic in Computer Science 3

Special Topic in Computer Science 4

Diploma Courses

Special Topic

Prerequisite: Permission of the Head of Department

Special Topic

Prerequisite: Permission of the Head of Department

Graduate Diploma Dissertation (Computer Science)

Restriction: COMPSCI 380

To complete this course students must enrol in COMPSCI 690 A and B

PG Diploma Dissertation (Computer Science)

Restriction: COMPSCI 780

To complete this course students must enrol in COMPSCI 691 A and B

Postgraduate 700 Level Courses

Advanced Topic in Computer Science 1

Prerequisite: Departmental approval

Advanced Topic in Computer Science 2

Prerequisite: Departmental approval

Advanced Topic in Computer Science 3

Prerequisite: Departmental approval

Advanced Topic in Computer Science 4

Prerequisite: Departmental approval

Advanced Topics in Human Computer Interaction

Human aspects of computer systems, relevant to commercial solution development and computer science research. Sample topics: support of pen-based interaction on a range of devices such as digital whiteboards, tablet PCs and PDAs; technical infrastructure for pen-based interaction; trends with domain specific user interface design, such as interfaces for enterprise systems.

Recommended preparation: COMPSCI 345 or SOFTENG 350

Prerequisite: Departmental approval

Restriction: SOFTENG 702

Advanced Topic in Computer Science 6

Prerequisite: Departmental approval

Advanced Topic in Computer Science 7

Prerequisite: Departmental approval

Advanced Topic in Computer Science 8

Prerequisite: Departmental approval

Advanced Topic in Computer Science 10

Prerequisite: Departmental approval

Parallel and Distributed Computing

Computer architectures and languages for exploring parallelism, conceptual models of parallelism, principles for programming in a parallel environment, different models to achieve interprocess communication, concurrency control, distributed algorithms and fault tolerance.

Recommended preparation: COMPSCI 335

Prerequisite: Departmental approval

Advanced Computer Graphics

An advanced look at current research issues in computer graphics. Typical topics include: ray-tracing acceleration methods; radiosity; subdivision surfaces; physically-based modelling; animation; image-based lighting and rendering; non-photorealistic rendering; advanced texturing. The precise content may vary from year to year. Consult the department for details.

Recommended preparation: COMPSCI 373 or equivalent, and 15 points at Stage II in Mathematics

Prerequisite: Departmental approval

Advanced Design and Analysis of Algorithms

Selected advanced topics in design and analysis of algorithms, such as: combinatorial enumeration algorithms; advanced graph algorithms; analytic and probabilistic methods in the analysis of algorithms; randomised algorithms; methods for attacking NP-hard problems.

Recommended preparation: COMPSCI 320

Prerequisite: Departmental approval

System Security

Data security: confidentiality, integrity, availability. System security: prohibitions, permissions, obligations, exemptions. The gold standard of dynamic security: authentication, audit, authorisation. Governance: specification, implementation, assurance. Three-layer defence: prevention, detection, response. Control modalities: architectural, economic, legal, normative. System-centric analyses: attacks, threats, vulnerabilities, information flows. Owner-centric analyses: functionality, security, trust, distrust. Data-centric analyses. Security techniques: encryption, obfuscation, tamper resistance. System designs.

Recommended preparation: 30 points from COMPSCI 313, 314, 320, 335, 340, 351, 702, 734, 742

Prerequisite: Departmental approval

Software Tools and Techniques

An advanced course examining research issues related to tools and techniques for software design and development. Typical topics include: techniques for data mapping and data integration, software architectures for developing software tools, issues in advanced database systems. The precise content may vary from year to year. Consult the department for details.

Recommended preparation: COMPSCI 335

Prerequisite: Departmental approval

Web, Mobile and Enterprise Computing

Examines advanced and emerging software architectures at the confluence of XML, web services, distributed systems, and databases. Includes advanced topics in areas such as: mobile computing, remoting, web services for enterprise integration, workflow orchestrations for the enterprise, peer-to-peer computing, grid computing.

Recommended preparation: COMPSCI 335

Prerequisite: Departmental approval

Advanced Internet: Global Data Communications

The protocols and performance of local area networks. The special requirements of very high speed networks (100 Mb/s and higher). Asynchronous transfer mode (ATM) and its relation to other protocols. The TCP/IP suite.

Recommended preparation: COMPSCI 314

Prerequisite: Departmental approval

Computational Complexity

Definitions of computational models and complexity classes: time complexity (eg, P and NP), space complexity (eg, L and PSPACE), circuit and parallel complexity (NC), polynomial-time hierarchy (PH), interactive complexity (IP), probabilistic complexity (BPP), and fixed-parameter complexity.

Recommended preparation: COMPSCI 320 or 350

Prerequisite: Departmental approval

Advanced Topics in Database Systems

Database principles. Relational model, relational algebra, relational calculus, SQL, SQL and programming languages, entity-relationship model, normalisation, query processing and query optimisation, ACID transactions, transaction isolation levels, database recovery, database security, databases and XML. Research frontiers in database systems.

Recommended preparation: COMPSCI 220, 225

Prerequisite: Departmental approval

Restriction: COMPSCI 351, SOFTENG 351

Datamining and Machine Learning

An overview of the learning problem and the view of learning by search. Techniques for learning such as: decision tree learning, rule learning, exhaustive learning, Bayesian learning, genetic algorithms, reinforcement learning, neural networks, explanation-based learning and inductive logic programming. Experimental methods necessary for understanding machine learning research.

Recommended preparation: COMPSCI 367

Prerequisite: Departmental approval

Advanced Topics in Artificial Intelligence

The cornerstones of AI: representation, utilisation, and acquisition of knowledge. Taking a real world problem and representing it in a computer so that the computer can do inference. Utilising this knowledge and acquiring new knowledge is done by search which is the main technique behind planning and machine learning. Research frontiers in artificial intelligence.

Recommended preparation: COMPSCI 220, 225

Prerequisite: Departmental approval

Restriction: COMPSCI 365, 366, 367

Intelligent Software Agents

An introduction to the design, implementation and use of intelligent software agents (eg, knowbots, softbots etc). Reviews standard artificial intelligence problem-solving paradigms (eg, planning and expert systems) and knowledge representation formalisms (eg, logic and semantic nets). Surveys agent architectures and multi-agent frameworks.

Recommended preparation: COMPSCI 367

Prerequisite: Departmental approval

Advanced Topics in Computer Graphics and Image Processing

Basic geometric processes including transformations; viewing and projection; back projection and ray tracing. Graphics modelling concepts: primitives, surfaces, and scene graphs, lighting and shading, texture mapping, and curve and surface design. Graphics and image processing fundamentals: image definition and representation, perception and colour models, grey level and colour enhancement, neighbourhood operations and filtering. Use of the OpenGL graphics pipeline. Research frontiers in computer graphics and image processing.

Recommended preparation: COMPSCI 210, 230

Prerequisite: Departmental approval

Restriction: COMPSCI 372, 373, 375

Intelligent Vision Systems

Computational methods and techniques for computer vision are applied to real-world problems such as 2/3D face biometrics, autonomous navigation, and vision-guided robotics based on 3D scene description. A particular feature of the course work is the emphasis on complete system design.

Recommended preparation: COMPSCI 373 and 15 points at Stage II in Mathematics

Prerequisite: Departmental approval

Advanced Multimedia Imaging

Camera calibration, image sequence analysis, computer vision, 3D visualisation, ground truth for image sequence analysis, performance evaluation (noise, accuracy). Applications in vision-based driver assistance, panoramic or 3D visualisation using recorded images, or image and video retrieval.

Recommended preparation: COMPSCI 373 and MATHS 208 or 250

Prerequisite: Departmental approval

Computer Games Technology

An advanced course looking at some of the computer graphics and artificial intelligence technology involved in computer games. Typical topics are: an introduction to the gaming industry; commercial modelling and animation software; maximising graphics performance, including such techniques as visibility preprocessing, multiple levels of detail, space subdivision, fast collision detection, direct programming of the graphics card; AI for computer games, including decision trees, rule-based systems, path planning, flocking behaviours, intelligent agents; research issues, such as physically-based modelling, terrain generation, computer learning.

Recommended preparation: COMPSCI 373, 367

Prerequisite: Departmental approval

Postgraduate Project in Computer Science 1

Prerequisite: Departmental approval

Restriction: COMPSCI 691

To complete this course students must enrol in COMPSCI 780 A and B, or COMPSCI 780

BSc(Hons) Dissertation

Prerequisite: Approval of Head of Department

To complete this course students must enrol in COMPSCI 789 A and B

History of Computing and Computers

A survey of the historical context of modern computing and information technology. History of computing and computing devices prior to the computer age. Developments in computing since the introduction of electronic computers. Significant software developments and applications of computers.

Recommended preparation: 60 points from Stage III Computer Science courses

Prerequisite: Departmental approval

MSc Thesis in Computer Science

To complete this course students must enrol in COMPSCI 796 A and B

---

Source: The University of Auckland 2012 Online Calendar
Last updated on: Tuesday 1 November 2011
Viewed on: