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Developing maintainable software has been an ongoing challenge in the software industry. This course presents the principles and practices that have been proposed for developing maintainable software systems. It will evaluate and critique these principles and practices through examining their application in practice and through understanding the research on their effectiveness. Recommended preparation: COMPSCI 331 or 718

Covers security features supported by the different platforms for smart devices. Provides an overview of the most popular OS platforms in the market and focuses on security for Android and iOS. Recommended preparation: COMPSCI 340

AI deep learning has significantly advanced image understanding, language modelling, speech recognition, game playing, and more. These developments enable near-human capabilities in text and image generation. Explores highly specialised knowledge in planning, reasoning, explanation, natural language understanding, and knowledge acquisition, and assess their contribution to highly competent, general AI systems. Includes a significant individual research project.

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

Human aspects of computer systems, relevant to commercial solution development and computer science research. Sample topics: advanced evaluation methods; support of pen and touch-based interaction; trends with domain specific user interface design, such as interfaces for enterprise systems.

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 320 or 335

Introduces students to a range of philosophical and normative topics relating to artificial intelligence. Examines key ideas of intelligence, privacy, consent, and discusses other ethical issues that arise in the development and use of AI. The importance of Māori rights and interests in AI and data are explored. Possible approaches to addressing these various concerns are considered.

Examines the core concepts and techniques in AI, including breakthroughs in symbolic AI, machine learning, and neural networks. Real-world applications are presented, with a focus on AI research in Aotearoa/NZ and ethical considerations. The course is designed to be accessible to students with limited programming experience.

Equips students with the ability to develop AI applications by introducing well-established AI frameworks and using web-based interactive computing platforms. Students will acquire the skills to implement simple AI techniques using these frameworks and evaluate their performance. Introduces basic practical technologies to investigate artificial intelligence techniques.

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. Recommended preparation: COMPSCI 373

Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: COMPSCI 120, 130

Fundamental techniques are covered for the design of algorithms such as greedy algorithms, divide-and-conquer, and dynamic programming. Data structures are explored that help implement algorithms. Essential tools are taught for analysing algorithms, for example worst- and average-case analyses of space and time. Recommended preparation: COMPSCI 120, 130

An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.

An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.

An examination of object-oriented programming and design. Key principles of object-oriented programming: typing, encapsulation, inheritance, polymorphism and composition. Fundamental object-oriented modelling and design techniques. Students will develop application software of reasonable complexity that draws on object-oriented language features, and contemporary APIs, frameworks and tools.

An examination of developing web-based applications. Client-side technologies: HTML, CSS and Javascript. Server-side technologies to support dynamic Web pages and data access. Fundamental relational database concepts and design techniques. Principles of Web-application design. HCI considerations and mobile clients. Students will build a Web-based application that dynamically generates content involving relational database access.

An examination of developing web-based applications. Client-side technologies: HTML, CSS and Javascript. Server-side technologies to support dynamic Web pages and data access. Fundamental relational database concepts and design techniques. Principles of Web-application design. HCI considerations and mobile clients. Students will build a Web-based application that dynamically generates content involving relational database access.

An examination of developing web-based applications. Client-side technologies: HTML, CSS and Javascript. Server-side technologies to support dynamic Web pages and data access. Fundamental relational database concepts and design techniques. Principles of Web-application design. HCI considerations and mobile clients. Students will build a Web-based application that dynamically generates content involving relational database access.

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

Randomised algorithms are algorithms that “flip coins” to make decisions. In many cases, such algorithms are faster, simpler, or more elegant than the classical, deterministic ones. Covers basic principles and techniques used to design and analyse randomised algorithms, and applications of randomised methods in mathematics and computer science. Recommended preparation: STATS 125, COMPSCI 225 or MATHS 254, COMPSCI 320

The human aspect of cyber security and privacy engineering is relevant to commercial solution development and cyber security and privacy research. Sample topics: secure systems design; usable security systems evaluation; privacy-preserving software systems; threat modelling; economics of usable security and privacy; OWASP Top 10 vulnerabilities. Recommended preparation: 30 points from COMPSCI 313, 314, 320, 335, 340, 351, 702, 734, 742

Focuses on the use and deployment of protective systems used in securing internal and external networks. Examines in detail the widely used protocols including SSL, IPSec, DNSSEC as well as covers infrastructure platform protocols including wireless security (IEEE 802.11). Explores current research and developments in the area of network defence and countermeasures. Recommended preparation: COMPSCI 314, 315

Builds on best practices, and compliance standards to establish an advanced understanding of modern cryptographic systems used in securing communications and data storage. Advanced knowledge in modern cryptography management issues such as algorithm selection, generation, distribution, and revocation of encryption keys are applied through a research-based report and a group project. Recommended preparation: COMPSCI 210 or MATHS 120

An advanced course examining research issues related to tools and techniques for software design and development. Topics include: techniques for data mapping and data integration, software architectures for developing software tools, issues in advanced database systems. Recommended preparation: COMPSCI 331 or SOFTENG 325 or COMPSCI 718 and 719

An overview of topics related to the use of technology in education and how people learn computer science concepts. Topics include research methodologies used in computer science education, how novices learn to program, and how technology can engage students in active learning, facilitate collaboration and enhance traditional educational practice. Recommended preparation: 30 points at Stage III in Computer Science or COMPSCI 718