Program Requirements
This program provides a more challenging and researchoriented version of the Major Software Engineering program.
Students may complete this program with a maximum of 75 credits or a minimum of 72 credits if they are exempt from taking COMP 202.
Honours students must maintain a CGPA of at least 3.00 during their studies and at graduation.
Required Courses
3942 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 2019, Winter 2020
Instructors: Elizabeth Patitsas, Giulia Alberini (Fall) Giulia Alberini (Winter)
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 2019, Winter 2020
Instructors: Joseph P Vybihal (Fall) 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 2019, Winter 2020
Instructors: Michael Langer, Giulia Alberini (Fall) 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 2019, Winter 2020
Instructors: Jérôme Waldispuhl (Fall)
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 2019, Winter 2020
Instructors: Joseph P Vybihal (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 2019, Winter 2020
Instructors: Brigitte Pientka, Jacob Errington (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 2019, Winter 2020
Instructors: Martin Robillard (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 2019, Winter 2020
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 2019
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 2020
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

COMP 400 Project in Computer Science (4 credits)
Overview
Computer Science (Sci) : A research project in any area of computer science, involving a programming effort and/or a theoretical investigation, and supervised by a faculty member in the School of Computer Science. Final written report required.
Terms: Fall 2019, Winter 2020
Instructors: Jorg Andreas Kienzle (Fall) Jorg Andreas Kienzle (Winter)
3 hours
Prerequisites: 15 Computer Science credits.
Restriction: For Honours students, or nonHonours students with permission of the department.

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 2019
Instructors: Katarzyna Radecka (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 2019, Winter 2020
Instructors: Djivede Kelome (Fall) Jeremy Macdonald (Winter)

MATH 240 Discrete Structures (3 credits)
Overview
Mathematics & Statistics (Sci) : Introduction to discrete mathematics and applications. Logical reasoning and methods of proof. Elementary number theory and cryptography: prime numbers, modular equations, RSA encryption. Combinatorics: basic enumeration, combinatorial methods, recurrence equations. Graph theory: trees, cycles, planar graphs.
Terms: Fall 2019, Winter 2020
Instructors: Jeremy Macdonald, Bogdan Nica (Fall) Jeremy Macdonald (Winter)
Complementary Courses (33 credits)
At least 9 credits must be from Groups A and B, with at least 3 credits from each:
At least 18 credits must be from Groups C and D, with at least 9 credits from Group C and at least 6 credits from Group D.
At least 12 credits must be from COMP courses at the 500 level or above.
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 2019, Winter 2020
Instructors: Jeremy Macdonald, Broderick Causley (Fall) Jérôme Fortier (Winter)

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 2019, Winter 2020
Instructors: Jose Andres Correa, Shomoita Alam (Fall) Djivede Kelome, David B Wolfson (Winter)

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 2019, Winter 2020
Instructors: Masoud AsgharianDastenaei (Fall)
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 2019
Instructors: Claude Crepeau (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 2019, Winter 2020
Instructors: Hamed Hatami (Fall) Adrian Roshan Vetta (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 2020
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 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 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 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 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: This course is not scheduled for the 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 academic year.
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: This course is not scheduled for the 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 academic year.

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 2019
Instructors: Shane McIntosh (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 2019
Instructors: Zeljko Zilic (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: Fall 2019
Instructors: Jeremy Cooperstock (Fall)

ECSE 437 Software Delivery (3 credits)
Overview
Electrical Engineering : Design, development, and implementation of code integration processes, release pipelines, and deployment strategies.
Terms: Fall 2019
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: This course is not scheduled for the 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 academic year.
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 2019
Instructors: Ivo Panayotov, Sitao Luan (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 2019
Instructors: David Meger (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 2020
Instructors: There are no professors associated with this course for the 20192020 academic year.

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 2020
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: This course is not scheduled for the 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 academic year.

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 2020
Instructors: There are no professors associated with this course for the 20192020 academic year.

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 2019
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 20192020 academic year.
Instructors: There are no professors associated with this course for the 20192020 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 2020
Instructors: Xue Liu (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 2019, Winter 2020
Instructors: William Hamilton (Fall) Reihaneh Rabbany, Mohsen Ravanbakhsh (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 2019
Instructors: Paul Kry (Fall)

COMP 558 Fundamentals of Computer Vision (4 credits)
Overview
Computer Science (Sci) : Image filtering, edge detection, image features and histograms, image segmentation, image motion and tracking, projective geometry, camera calibration, homographies, epipolar geometry and stereo, point clouds and 3D registration. Applications in computer graphics and robotics.
Terms: Fall 2019
Instructors: Kaleem Siddiqi (Fall)