Program Requirements
This program provides a broad introduction to the principles of computer science and covers in depth the design and development of software systems.
Students may complete this program with a maximum of 63 credits or a minimum of 60 credits if they are exempt from taking COMP 202.
Required Courses
3639 credits
* Students who have sufficient knowledge in a programming language do not need to take COMP 202.

COMP 202 Foundations of Programming (3 credits) *
Overview
Computer Science (Sci) : Introduction to computer programming in a high level language: variables, expressions, primitive types, methods, conditionals, loops. Introduction to algorithms, data structures (arrays, strings), modular software design, libraries, file input/output, debugging, exception handling. Selected topics.
Terms: Fall 2018, Winter 2019, Summer 2019
Instructors: Giulia Alberini, Joseph P Vybihal (Fall) Giulia Alberini, TzuYang Yu (Winter) TzuYang Yu (Summer)
3 hours
Prerequisite: a CEGEP level mathematics course
Restrictions: COMP 202 and COMP 208 cannot both be taken for credit. COMP 202 is intended as a general introductory course, while COMP 208 is intended for students interested in scientific computation. COMP 202 cannot be taken for credit with or after COMP 250

COMP 206 Introduction to Software Systems (3 credits)
Overview
Computer Science (Sci) : Comprehensive overview of programming in C, use of system calls and libraries, debugging and testing of code; use of developmental tools like make, version control systems.
Terms: Fall 2018, Winter 2019
Instructors: David Meger (Fall) Chad Zammar, Joseph P Vybihal (Winter)

COMP 250 Introduction to Computer Science (3 credits)
Overview
Computer Science (Sci) : Mathematical tools (binary numbers, induction, recurrence relations, asymptotic complexity, establishing correctness of programs), Data structures (arrays, stacks, queues, linked lists, trees, binary trees, binary search trees, heaps, hash tables), Recursive and nonrecursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Terms: Fall 2018, Winter 2019
Instructors: Michael Langer, Giulia Alberini (Fall) Martin Robillard, Giulia Alberini (Winter)

COMP 251 Algorithms and Data Structures (3 credits)
Overview
Computer Science (Sci) : Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.
Terms: Fall 2018, Winter 2019
Instructors: Jérôme Waldispuhl (Fall) Luc P Devroye, Erin Leigh McLeish (Winter)
3 hours
Prerequisite: COMP 250
COMP 251 uses mathematical proof techniques that are taught in the corequisite course(s). If possible, students should take the corequisite course prior to COMP 251.
COMP 251 uses basic counting techniques (permutations and combinations) that are covered in MATH 240 and 363, but not in MATH 235. These techniques will be reviewed for the benefit of MATH 235 students.
Restrictions: Not open to students who have taken or are taking COMP 252.

COMP 273 Introduction to Computer Systems (3 credits)
Overview
Computer Science (Sci) : Number representations, combinational and sequential digital circuits, MIPS instructions and architecture datapath and control, caches, virtual memory, interrupts and exceptions, pipelining.
Terms: Fall 2018, Winter 2019
Instructors: Paul Kry (Fall) Kaleem Siddiqi (Winter)
3 hours
Corequisite: COMP 206.

COMP 302 Programming Languages and Paradigms (3 credits)
Overview
Computer Science (Sci) : Programming language design issues and programming paradigms. Binding and scoping, parameter passing, lambda abstraction, data abstraction, type checking. Functional and logic programming.
Terms: Fall 2018, Winter 2019
Instructors: Brigitte Pientka (Fall) Prakash Panangaden (Winter)
3 hours
Prerequisite: COMP 250

COMP 303 Software Design (3 credits)
Overview
Computer Science (Sci) : Principles, mechanisms, techniques, and tools for objectoriented software design and its implementation, including encapsulation, design patterns, and unit testing.
Terms: Fall 2018, Winter 2019
Instructors: Mathieu Nassif, Joseph P Vybihal (Fall) Jin Guo (Winter)

COMP 310 Operating Systems (3 credits)
Overview
Computer Science (Sci) : Control and scheduling of large information processing systems. Operating system software  resource allocation, dispatching, processors, access methods, job control languages, main storage management. Batch processing, multiprogramming, multiprocessing, time sharing.
Terms: Fall 2018, Winter 2019
Instructors: Muthucumaru Maheswaran (Fall) Joseph P Vybihal (Winter)
3 hours
Prerequisite: COMP 273

COMP 361D1 Software Engineering Project (3 credits)
Overview
Computer Science (Sci) : Software development process in practice: requirement elicitation and analysis, software design, implementation, integration, test planning, and maintenance. Application of the core concepts and techniques through the realization of a large software system.
Terms: Fall 2018
Instructors: Jorg Andreas Kienzle (Fall)
Corequisite: COMP 303
Restriction: Not open to students who have taken the 3 credit version of COMP 361.
Students must register for both COMP 361D1 and COMP 361D2
No credit will be given for this course unless both COMP 361D1 and COMP 361D2 are successfully completed in consecutive terms

COMP 361D2 Software Engineering Project (3 credits)
Overview
Computer Science (Sci) : See COMP 361D1 for course description.
Terms: Winter 2019
Instructors: Jorg Andreas Kienzle (Winter)
Prerequisite: COMP 361D1
No credit will be given for this course unless both COMP 361D1 and COMP 361D2 are successfully completed in consecutive terms

ECSE 429 Software Validation (3 credits)
Overview
Electrical Engineering : Correct and complete implementation of software requirements. Verification and validation lifecycle. Requirements analysis, model based analysis, and design analysis. Unit and system testing, performance, risk management, software reuse. Ubiquitous computing.
Terms: Fall 2018
Instructors: Daniel Varro (Fall)

MATH 223 Linear Algebra (3 credits)
Overview
Mathematics & Statistics (Sci) : Review of matrix algebra, determinants and systems of linear equations. Vector spaces, linear operators and their matrix representations, orthogonality. Eigenvalues and eigenvectors, diagonalization of Hermitian matrices. Applications.
Terms: Fall 2018, Winter 2019
Instructors: Djivede Kelome (Fall) Jeremy Macdonald (Winter)

MATH 240 Discrete Structures 1 (3 credits)
Overview
Mathematics & Statistics (Sci) : Mathematical foundations of logical thinking and reasoning. Mathematical language and proof techniques. Quantifiers. Induction. Elementary number theory. Modular arithmetic. Recurrence relations and asymptotics. Combinatorial enumeration. Functions and relations. Partially ordered sets and lattices. Introduction to graphs, digraphs and rooted trees.
Terms: Fall 2018, Winter 2019
Instructors: Jeremy Macdonald, Bogdan Nica (Fall) Jeremy Macdonald, Yann Batiste Pequignot (Winter)
Complementary Courses (24 credits)
9 credits selected from Groups A and B, with at least 3 credits selected from each:
15 credits selected from Groups C and D, with at least 9 credits selected from Group C, and at least 3 credits selected from Group D.
Group A:

MATH 222 Calculus 3 (3 credits)
Overview
Mathematics & Statistics (Sci) : Taylor series, Taylor's theorem in one and several variables. Review of vector geometry. Partial differentiation, directional derivative. Extreme of functions of 2 or 3 variables. Parametric curves and arc length. Polar and spherical coordinates. Multiple integrals.
Terms: Fall 2018, Winter 2019, Summer 2019
Instructors: Jeremy Macdonald, Dmitry Faifman (Fall) Lars Sektnan (Winter) Yann Batiste Pequignot (Summer)

MATH 323 Probability (3 credits)
Overview
Mathematics & Statistics (Sci) : Sample space, events, conditional probability, independence of events, Bayes' Theorem. Basic combinatorial probability, random variables, discrete and continuous univariate and multivariate distributions. Independence of random variables. Inequalities, weak law of large numbers, central limit theorem.
Terms: Fall 2018, Winter 2019, Summer 2019
Instructors: David Stephens (Fall) David B Wolfson (Winter) Djivede Kelome (Summer)

MATH 324 Statistics (3 credits)
Overview
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2018, Winter 2019
Instructors: Abbas Khalili Mahmoudabadi (Fall) Masoud AsgharianDastenaei (Winter)
Fall and Winter
Prerequisite: MATH 323 or equivalent
Restriction: Not open to students who have taken or are taking MATH 357
You may not be able to receive credit for this course and other statistic courses. Be sure to check the Course Overlap section under Faculty Degree Requirements in the Arts or Science section of the Calendar.
Group B:

COMP 330 Theory of Computation (3 credits)
Overview
Computer Science (Sci) : Finite automata, regular languages, contextfree languages, pushdown automata, models of computation, computability theory, undecidability, reduction techniques.
Terms: Fall 2018
Instructors: Prakash Panangaden (Fall)
3 hours
Prerequisite: COMP 251.

COMP 360 Algorithm Design (3 credits)
Overview
Computer Science (Sci) : Advanced algorithm design and analysis. Linear programming, complexity and NPcompleteness, advanced algorithmic techniques.
Terms: Fall 2018, Winter 2019
Instructors: Bruce Alan Reed (Fall) Bruce Alan Reed (Winter)
Group C: Software Engineering Specialization
* Students may select either COMP 409 or ECSE 420, but not both.

COMP 409 Concurrent Programming (3 credits) *
Overview
Computer Science (Sci) : Characteristics and utility of concurrent programs; formal methods for specification, verification and development of concurrent programs; communications, synchronization, resource allocation and management, coherency and integrity.
Terms: Winter 2019
Instructors: Clark Verbrugge (Winter)

COMP 523 Languagebased Security (3 credits)
Overview
Computer Science (Sci) : Stateoftheart languagebased techniques for enforcing security policies in distributed computing environments. Static techniques (such as type and proofchecking technology), verification of security policies and applications such as proofcarrying code, certifying compilers, and proofcarrying authentication.
Terms: This course is not scheduled for the 20182019 academic year.
Instructors: There are no professors associated with this course for the 20182019 academic year.

COMP 525 Formal Verification (3 credits)
Overview
Computer Science (Sci) : Propositional logic  syntax and semantics, temporal logic, other modal logics, model checking, symbolic model checking, binary decision diagrams, other approaches to formal verification.
Terms: This course is not scheduled for the 20182019 academic year.
Instructors: There are no professors associated with this course for the 20182019 academic year.

COMP 529 Software Architecture (4 credits)
Overview
Computer Science (Sci) : Development, analysis, and maintenance of software architectures, with special focus on modular decomposition and reverse engineering.
Terms: Winter 2019
Instructors: Martin Robillard (Winter)
4 hours
Prerequisite: COMP 303.

COMP 533 ModelDriven Software Development (3 credits)
Overview
Computer Science (Sci) : Modeldriven software development; requirements engineering based on use cases and scenarios; objectoriented modelling using UML and OCL to establish complete and precise analysis and design documents; mapping to Java. Introduction to metamodelling and model transformations, use of modelling tools.
Terms: Fall 2018
Instructors: Jorg Andreas Kienzle (Fall)

ECSE 326 Software Requirements Engineering (3 credits)
Overview
Electrical Engineering : Techniques for eliciting requirements; languages and models for specification of requirements; analysis and validation techniques, including featurebased, goalbased, and scenariobased analysis; quality requirements; requirements traceability and management; handling evolution of requirements; requirements documentation standards; requirements in the context of system engineering; integration of requirements engineering into software engineering processes.
Terms: Fall 2018
Instructors: Gunter Mussbacher (Fall)

ECSE 420 Parallel Computing (3 credits) *
Overview
Electrical Engineering : Modern parallel computing architectures for shared memory, message passing and data parallel programming models. The design of cache coherent shared memory multiprocessors. Programming techniques for multithreaded, message passing and distributed systems. Use of modern programming languages and parallel programming libraries.
Terms: Fall 2018
Instructors: Dennis Giannacopoulos (Fall)
(324)
Prerequisite: ECSE 427

ECSE 424 HumanComputer Interaction (3 credits)
Overview
Electrical Engineering : The course highlights humancomputer interaction strategies from an engineering perspective. Topics include user interfaces, novel paradigms in humancomputer interaction, affordances, ecological interface design, ubiquitous computing and computersupported cooperative work. Attention will be paid to issues of safety, usability, and performance.
Terms: This course is not scheduled for the 20182019 academic year.
Instructors: There are no professors associated with this course for the 20182019 academic year.

ECSE 437 Software Delivery (3 credits)
Overview
Electrical Engineering : Design, development, and implementation of code integration processes, release pipelines, and deployment strategies.
Terms: Fall 2018
Instructors: Shane McIntosh (Fall)

ECSE 539 Advanced Software Language Engineering (4 credits)
Overview
Electrical Engineering : Practical and theoretical knowledge for developing software languages and models; foundations for modelbased software development; topics include principles of modeldriven engineering; concerndriven development; intentional, structural, and behavioral models as well as configuration models; constraints; language engineering; domainspecific languages; metamodelling; model transformations; models of computation; model analyses; and modeling tools.
Terms: Fall 2018
Instructors: Gunter Mussbacher (Fall)
Group D: Applications

COMP 350 Numerical Computing (3 credits)
Overview
Computer Science (Sci) : Computer representation of numbers, IEEE Standard for Floating Point Representation, computer arithmetic and rounding errors. Numerical stability. Matrix computations and software systems. Polynomial interpolation. Leastsquares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.
Terms: Fall 2018
Instructors: XiaoWen Chang (Fall)

COMP 417 Introduction Robotics and Intelligent Systems (3 credits)
Overview
Computer Science (Sci) : This course considers issues relevant to the design of robotic and of intelligent systems. How can robots move and interact. Robotic hardware systems. Kinematics and inverse kinematics. Sensors, sensor data interpretation and sensor fusion. Path planning. Configuration spaces. Position estimation. Intelligent systems. Spatial mapping. Multiagent systems. Applications.
Terms: Fall 2018
Instructors: Gregory L Dudek (Fall)

COMP 421 Database Systems (3 credits)
Overview
Computer Science (Sci) : Database Design: conceptual design of databases (e.g., entityrelationship model), relational data model, functional dependencies. Database Manipulation: relational algebra, SQL, database application programming, triggers, access control. Database Implementation: transactions, concurrency control, recovery, query execution and query optimization.
Terms: Winter 2019
Instructors: Joseph D'silva (Winter)

COMP 424 Artificial Intelligence (3 credits)
Overview
Computer Science (Sci) : Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.
Terms: Winter 2019
Instructors: Jackie Cheung (Winter)

COMP 512 Distributed Systems (4 credits)
Overview
Computer Science (Sci) : Models and Architectures. Applicationoriented communication paradigms (e.g. remote method invocation, group communication). Naming services. Synchronization (e.g. mutual exclusion, concurrency control). Faulttolerance (e.g. process and replication, agreement protocols). Distributed file systems. Security. Examples of distributed systems (e.g. Web, CORBA). Advanced Topics.
Terms: Fall 2018
Instructors: Bettina Kemme (Fall)

COMP 520 Compiler Design (4 credits)
Overview
Computer Science (Sci) : The structure of a compiler. Lexical analysis. Parsing techniques. Syntax directed translation. Runtime implementation of various programming language constructs. Introduction to code generation for an idealized machine. Students will implement parts of a compiler.
Terms: Winter 2019
Instructors: Alexander Krolik (Winter)

COMP 521 Modern Computer Games (4 credits)
Overview
Computer Science (Sci) : Genre and history of games, basic game design, storytelling and narrative analysis, game engines, design of virtual worlds, realtime 2D graphics, game physics and physical simulation, pathfinding and game AI, content generation, 3D game concerns, multiplayer and distributed games, social issues.
Terms: Fall 2018
Instructors: Clark Verbrugge (Fall)

COMP 522 Modelling and Simulation (4 credits)
Overview
Computer Science (Sci) : Simulation and modelling processes, state automata, Petri Nets, state charts, discrete event systems, continuoustime models, hybrid models, system dynamics and objectoriented modelling.
Terms: This course is not scheduled for the 20182019 academic year.
Instructors: There are no professors associated with this course for the 20182019 academic year.

COMP 535 Computer Networks 1 (4 credits)
Overview
Computer Science (Sci) : Fundamental design principles, elements, and protocols of computer networks, focusing on the current Internet. Topics include: layered architecture, direct link networks, switching and forwarding, bridge routing, congestion control, endtoend protocols application of DNS, HTTP, P2P, fair queuing, performance modeling and analysis.
Terms: Winter 2019
Instructors: Diala Naboulsi (Winter)

COMP 551 Applied Machine Learning (4 credits)
Overview
Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.
Terms: Fall 2018, Winter 2019
Instructors: Sarath Chandar (Fall) William Hamilton (Winter)

COMP 557 Fundamentals of Computer Graphics (4 credits)
Overview
Computer Science (Sci) : Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, linedrawing and rasterization, hidden surface removal, surface modelling (quadrics, bicubics, meshes), rendering (lighting, reflectance models, ray tracing, texture mapping), compositing colour perception, and other selected topics.
Terms: Fall 2018
Instructors: Paul Kry (Fall)

COMP 558 Fundamentals of Computer Vision (3 credits)
Overview
Computer Science (Sci) : Biological vision, edge detection, projective geometry and camera modelling, shape from shading and texture, stereo vision, optical flow, motion analysis, object representation, object recognition, graph theoretic methods, high level vision, applications.
Terms: Fall 2018
Instructors: Kaleem Siddiqi, Michael Langer (Fall)