Computer Science

The principles, processes, and applications of software reliability and software quality assurance.

Exploration of various areas in Computer Science. Topics will vary from year-to-year. Offered as required to provide opportunities for students to engage in additional areas in Computer Science.

Attacks on networked systems and Internet protocols. Tools and techniques for detection and protection against attacks including firewalls, authentication, and cryptographic protocols. Web security attacks and defenses including same-origin policy, cross site scripting, and UI redressing. Legal and ethical issues will be introduced.

Standard techniques for the implementation of computer games. Standard multimedia programming environments and high performance multimedia. Special purpose rendering engines. Interactive control and feedback; modelling. Prequisites: Computer Science 453 and consent of the Department.

An extensive treatment of differential and integral calculus in a single variable, with an emphasis on applications. Differentiation: derivative laws, the mean value theorem, optimization, curve sketching and other applications. Integral calculus: the fundamental theorem of calculus, techniques of integration, improper integrals, and areas of planar regions. Infinite series: power series, Taylor's theorem and Taylor series.

An introduction to the modelling and simulation of stochastic systems; programming language issues; model and tool design; input data modelling; simulation experiments; and the interpretation of simulation results.

Information theoretic concepts such as entropy and mutual information and their applications to defining and evaluating information security systems including encryption, authentication, secret sharing and secure message transmission.

Exploration of various areas in Computer Science. Topics will vary from year-to-year. It will be offered as required to provide the opportunity for students to engage in additional areas in Computer Science.

Introduction to data mining with emphasis on frequent pattern mining, clustering and classification, data collection, network construction, basic graph theory concepts and network analysis metrics, and case studies.

Security policies and protection mechanisms for a computing system, including such topics as design principles of protection systems, authentication and authorization, reference monitors, security architecture of popular platforms, formal modelling of protection systems, discretionary access control, safety analysis, information flow control, integrity, role-based access control. Legal and ethical considerations will be introduced.

Exploration of various areas in Computer Science. Topics will vary from year-to-year. It will be offered as required to provide the opportunity for students to engage in additional areas in Computer Science.

An insight into a new mindset for programming as an emergent and evolutionary process. Programs can evolve and learn as a result of training and emergency from augmented intelligence systems properties rather than being manually coded. Topics will include: agent-based programming, emergent augmented intelligence, evolutionary algorithms, swarm intelligence, neural networks and other bio-inspired methodologies for constructing intelligent systems.

An exploration of the breadth of computer science including both classical subjects and topics of current and ongoing interest. The focus of the course is on examining and appreciating how computers accomplish tasks we commonly perform. It is not expected that students use mathematics or programming.

Basic problems in distributed systems such as symmetry breaking, consensus, resource allocation, and synchronization. The impact of system characteristics, such as models of communication, timing and failure, and of solution requirements, such as correctness and complexity criteria and algorithmic constraints, on the computability and complexity of these problems. Techniques for solving problems under different models will be emphasized.

Theory and application of advanced programming methods and tools. Recent issues as well as those of an enduring nature will be discussed. Topics may include the Fourier transform; wavelets; functional programming; genetic algorithms, simulated annealing and neural networks; parallel and distributed programming; images and graphics user interface programming.

Introduction to the design, implementation and evaluation of human-robot interfaces. Topics include the evaluation of human-robot interaction (HRI), theoretical, philosophical and ethical issues, exploration of applications and tasks, prototyping HRI tools, and practical implementation and evaluation methods.

AI techniques commonly used in video games, such as behaviour trees, search-based methods, and machine learning. Implementation of AI techniques in a commercial game engine.

Analyzing quality requirements of large-scale software. Performance analysis, testing, and tuning techniques. Evaluating software scalability. Capacity planning methodologies. Issues related to safety, security, and availability of software.

Time and space complexity; the classes P, LOGSPACE, PSPACE and their nondeterministic counterparts; containments and separations between complexity classes; intractability and the theory of NP-completeness; complexity theories for probabilistic algorithms and for parallel algorithms.

Theoretical foundations of functional programming: the lambda-calculus, beta-reduction, confluence, and reduction strategies. Programming syntax: solving recursive equations with the Y-combinator, let and letrec, types, datatypes, and patterns. Programming in a functional language: recursion patterns, useful combinators, maps, and folds, for datatypes. Example applications: recursive descent parsing, unification, combinatorial algorithms, theorem proving.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

Principles and practice in modern telecommunications, computer communications and networks. Layered communication protocols and current physical, data link, network and Internet protocol layers. Circuit switching, packet switching, and an introduction to broadband multimedia networking.

The basics of cryptography, with emphasis on attaining well-defined and practical notions of security. Symmetric and public-key cryptosystems; one-way and trapdoor functions; mechanisms for data integrity; digital signatures; key management; applications to the design of cryptographic systems. Assessment will primarily focus on mathematical theory and proof-oriented homework problems; additional application programming exercises will be available for extra credit.

Software architectures and design for non-functional software properties. Introduction to program comprehension skills including analysis of existing architectures.

Exploration of various areas in Computer Science. Topics will vary from year to year. It will be offered as required to provide the opportunity for students to engage in additional areas in Computer Science.

A research project conducted under the guidance of a faculty member. A report must be presented on completion of the course.

Concepts, methods, techniques, processes, and tools for software testing.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

An accelerated introduction to problem solving, the analysis and design of small-scale computational systems and implementation using both procedural and object-oriented programming languages. Issues of design, modularization, and programming style will be emphasized.

Design and implementation of modern database systems, including storage and indexing, query modification/optimization, recovery, concurrency, integrity, and distribution. Emphasis on data analysis, blockchain databases, and NoSQL databases.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

Exploration of various areas in Computer Science. Topics will vary from year-to-year. Offered as required to provide opportunities for students to engage in additional areas in Computer Science

Concepts, methods, techniques, processes, and tools for software testing. The principles, processes, and applications of software reliability and software quality assurance.

Study of computer viruses, worms, Trojan horses, and other forms of malicious software. Countermeasures to malicious software. Legal and ethical issues, and some general computer and network security issues.

Application of formal methods and mathematical logic to the modelling of access control systems and the design of policy languages. Topics include safety and resiliency analysis, proof of policy compliance, expressiveness of policy languages, policy analysis, as well as a survey of modern paradigms of access control.

Remain current in Computer Science as this field evolves by developing a reflective life-long learning practice. Independent student work will include using a wide variety of sources and developing the ability to self-assess progress in learning and knowledge in topics related to Computer Science.

A research project conducted under the guidance of a faculty member. A report must be presented on completion of the course.

Special topics at an introductory level on software development methods, technologies, or tools.

Parametric Modelling. B-splines and NURBS. Subdivision schemes. Surface subdivision. Multiresolution. Wavelets. Implicit modelling. Blends. Polygonization. Blobtree. Precise contact modelling. Solid modelling. CSG. Procedural modelling. Special topics, e.g. Differential geometry. Graph-based modelling. Topology.

Principles of traditional animation, key framing, parametric and track animation, free form deformation, inverse kinematics, dynamics, spring mass systems, particle systems, numerical integration, Lagrangian constraints, space time constraints, collisions, human animation, behavioural animation, metamorphosis, implicit animation techniques, animating liquids, gases and cloth, motion capture.

A research project conducted under the guidance of a faculty member. A report must be presented on completion of the course.

Interpolation and approximation, numerical integration and differentiation, numerical methods for the solution of non-linear equations, systems of linear equations and the eigenvalue problem, introduction to a scientific computing software.

A software engineering project conducted under the guidance of a faculty member.

Introduction to elicitation, modelling, expression and validation of the requirements. Techniques and methodologies for requirements engineering. Applications of requirements engineering to the management of the software development lifecycle.

Intermediate and advanced topics and applications in human-computer interaction, to further one's skills for designing highly interactive human-computer interfaces.

A survey of artificial intelligence and machine learning tools to cultivate an understanding of their capability, utility, and societal/ethical/legal considerations. Popular APIs will be used to develop simple applied examples.

Introduction to problem solving, analysis and design of small-scale computational systems and implementation using a procedural programming language. For students wishing to combine studies in computer science with studies in other disciplines.

New areas in Computer Science. This full course will be offered only as required. Before registration consult the Head of the Department of Computer Science for topics offered.

Creative design strategies, technical implementation approaches, interaction techniques, evaluation methods, and reflective practices for visualizing novel datasets. Exploration of specialized approaches including geospatial, network, text, and uncertainty visualization.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

Presenting various techniques for learning various kinds of knowledge, including rules, parameters, trees and graphs, partitions of sets, sequences and behaviors, and cases. Pointing out the components that can be improved using knowledge about the application area of a system. Looking at various pre-processing and post-processing improvement techniques.

An examination of communication paradigms in multi-agent systems. A number of paradigms will be covered including simple protocols, BDI (Believe, Desire, Intention), and social commitments.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

Theory and practice of designing tangible user interfaces and physical computing systems.

File architecture and manipulation techniques for various file types. Physical characteristics of current mass storage devices. Advanced data structures and algorithms for implementing various sequential and hierarchical file structures. File organization and design for various applications, file systems and other storage management techniques including website design.

Advanced techniques for the design and analysis of deterministic and probabilistic algorithms; techniques for deriving lower bounds on the complexity of problems.

An introduction to abstract models of sequential computation, including finite automata, regular expressions, context-free grammars, and Turing machines. Formal languages, including regular, context-free, and recursive languages, methods for classifying languages according to these types, and relationships among these classes.

Elementary techniques for the numerical solution of mathematical problems on a computer, including methods for solving linear and non-linear equations, numerical integration, and interpolation.

A hands-on introduction to basic coding skills, including core programming concepts and the fundamentals of reading, writing, and executing code -- with a focus on data manipulation. Emphasizes important tools and practices for programming with data, including development environments, source control, and debugging.

Phenomena and approaches involved in the evolution and reuse of large-scale software, including design for modifiability and tool support. Strengths and weaknesses of industrially-current techniques as well as recent research results.

Continuation of Introduction to Computer Science for Multidisciplinary Studies I. Emphasis on object-oriented analysis and design of small-scale computational systems and implementation using an object-oriented language. Issues of design, modularization and programming style will be emphasized.

Application of advanced algorithms and data structures to solve mathematical, logical, and computational puzzles; design principles, optimization, implementation, and strategies for collaborative problem solving.

Exploration of various areas in Computer Science. Topics will vary from year-to-year. It will be offered as required to provide the opportunity for students to engage in additional areas in Computer Science.

Fundamental problems, classical and modern algorithms, and algorithm design and analysis techniques of use in computer algebra. Integer and polynomial arithmetic. Additional problems in computer algebra, possibly including problems in computational linear algebra, factorization, and concerning systems of polynomial equations will be considered as time permits.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

The basics of cryptography, with emphasis on attaining well-defined and practical notations of security. Symmetric and public key cryptosystems; one-way and trapdoor functions; mechanisms for data integrity; digital signatures; key management; applications to the design of cryptographic systems. In addition to written homework, assessment will involve application programming; additional mathematical theory and proof-oriented exercises will be available for extra credit.

Introduction to quantum computing. Quantum algorithms, quantum search, quantum fourier transforms, quantum error correcting codes, quantum cryptography, nonlocality and quantum communication complexity, and quantum computational complexity.

Designing and implementing distributed systems that overcome challenges due to concurrent computation, failure of components in the system and heterogeneity of processors and communication channels.

Introduction to the theory and practice of data visualization with a focus on perception-based encoding choices and data mapping, chart authoring paradigms, visualization ethics and interpretation, and visual communication.

Software specification, verification, and validation using a mathematically rigorous technique.

An introduction to fundamental data structures, including lists, stacks, trees, hash tables, and graphs, and their application for data processing, analysis, and storage. Covers the fundamental state of the art data modelling and manipulation techniques, with emphasis on emerging characteristics of big data, including volume, velocity, variety and veracity.

A research project conducted under the guidance of a faculty member. A report must be presented on completion of the course.

Principles of machine learning in biometric system design. Examine methods of expert decision making in multi-modal systems using rank, score, decision and fuzzy level fusion. Biometric classification using traditional machine learning methods and modern deep learning architectures. Application topics may include image processing, pattern recognition, data mining, medicine, defense and cybersecurity.

Numerical solution of ordinary differential equations, single and multi-step methods, numerical solution of boundary value problems, numerical solution of partial differential equations, stability analysis.

Techniques for the design and analysis of randomized algorithms; discrete probability theory; randomized data structures; lower bound techniques; randomized complexity classes; advanced algorithmic applications from various areas.

Computable functions; decidable and undecidable problems; Church's thesis and recursive functions.

A substantial research project under the guidance of a faculty member. A report must be written and presented on completion of the course.

Topics and practices in systems administration and management. Required and optional administration duties and responsibilities. Moral and ethical conundrums, and legal responsibilities, in systems operation. Configuration and installation of operating systems and network and systems services.

Modelling of agents and properties of multi-agent systems. Communication issues, including interaction and co-ordination concepts, forming and maintaining organizations, and competitive agent environments. Example systems; the implementation of a multi-agent system will be performed as the assignment.

Standard methods used in the analysis of digital images. Image acquisition and display: visual perception; digital representation. Sampling and enhancement. Feature extraction and classification methods. Object recognition.

Analysis of methods, tools, and techniques for software project management as an effort to achieve quality software products.

Development of business models, building software prototypes and creation of pitch presentations to create a software-based business.

A continuation of Computer Science 331. Collision resolution in hash tables, search algorithms, advanced tree structures, strings. Advanced algorithmic tools for storing and manipulation of information.

Concepts and implementation of database models with emphasis on the relational paradigm: relational model, relational algebra and calculus, SQL query language, normalization theory, integrity and consistency. Overview of NoSQL databases and big data.

A substantial research, development, or entrepreneurial project for teams of computer science students. Research and development teams will work for internal or external clients. Entrepreneurial teams will work towards the creation of a computer science startup.

Fundamental theory and practice of the design, implementation, and evaluation of human-computer interfaces. Topics include: principles of design; methods for evaluating interfaces with or without user involvement; techniques for prototyping and implementing graphical user interfaces.

An examination of the objectives, key techniques and achievements of work on artificial intelligence in Computer Science.

An introduction to hardware and microprocessor design, including the connection between gate-level digital logic circuits and sequential machines that can execute an algorithm and perform input and output.

A research project conducted under the guidance of a faculty member. A report must be presented on completion of the course.

A broad survey of topics in information security and privacy, with the purpose of cultivating an appropriate mindset for approaching security and privacy issues. Topics will be motivated by recreational puzzles. Legal and ethical considerations will be introduced as necessary.

Spam and other unsolicited bulk electronic communication, and spyware. Legal and ethical issues. Countermeasures and related security problems.