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Note: This is the 2022–2023 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
Note: This is the 2022–2023 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
This program provides a more challenging and research-oriented 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.
39-42 credits
* Students who have sufficient knowledge in a programming language do not need to take COMP 202.
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 2022, Winter 2023, Summer 2023
Instructors: Campbell, Jonathan (Fall) M'hiri, Faten (Winter) M'hiri, Faten (Summer)
3 hours
Prerequisite: a CEGEP level mathematics course
Restrictions: Not open to students who have taken or are taking COMP 204, COMP 208, or GEOG 333; not open to students who have taken or are taking COMP 206 or COMP 250.
COMP 202 is intended as a general introductory course, while COMP 204 is intended for students in life sciences, and COMP 208 is intended for students in physical sciences and engineering.
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 2022, Winter 2023
Instructors: D'silva, Joseph (Fall) Errington, Jacob; Vybihal, Joseph P (Winter)
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 non-recursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Terms: Fall 2022, Winter 2023
Instructors: Alberini, Giulia (Fall) Alberini, Giulia (Winter)
Computer Science (Sci) : Introduction to algorithm design and analysis. Graph algorithms, greedy algorithms, data structures, dynamic programming, maximum flows.
Terms: Fall 2022, Winter 2023
Instructors: Waldispuhl, Jérôme; Alberini, Giulia (Fall) Becerra, David (Winter)
3 hours
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 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.
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 2022, Winter 2023
Instructors: Vybihal, Joseph P (Fall) Kry, Paul; Elsaadawy, Mona (Winter)
3 hours
Corequisite: COMP 206.
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 2022, Winter 2023
Instructors: Errington, Jacob (Fall) Errington, Jacob (Winter)
Computer Science (Sci) : Principles, mechanisms, techniques, and tools for object-oriented software design and its implementation, including encapsulation, design patterns, and unit testing.
Terms: Fall 2022, Winter 2023
Instructors: Robillard, Martin (Fall) Guo, Jin (Winter)
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 2022, Winter 2023
Instructors: Maheswaran, Muthucumaru (Fall) Balmau, Oana (Winter)
3 hours
Prerequisite: COMP 273
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 2022
Instructors: Schiedermeier, Maximilian (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
Computer Science (Sci) : See COMP 361D1 for course description.
Terms: Winter 2023
Instructors: Schiedermeier, Maximilian (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
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 2022, Winter 2023, Summer 2023
Instructors: M'hiri, Faten (Fall) Errington, Jacob (Winter) Errington, Jacob (Summer)
3 hours
Prerequisites: 15 Computer Science credits.
Restriction: For Honours students, or non-Honours students with permission of the department.
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 2022, Winter 2023
Instructors: Varro, Daniel (Fall) Sabourin, Robert (Winter)
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 2022, Winter 2023
Instructors: Macdonald, Jeremy; Pichot, Mikael (Fall) Macdonald, Jeremy (Winter)
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 2022, Winter 2023
Instructors: Vetta, Adrian Roshan; Fortier, Jérôme (Fall) Fortier, Jérôme; Macdonald, Jeremy (Winter)
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.
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 2022, Winter 2023, Summer 2023
Instructors: Paquette, Elliot; Wrobel, Konrad (Fall) Trudeau, Sidney (Winter) Barill, Gavin (Summer)
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 2022, Winter 2023, Summer 2023
Instructors: Nadarajah, Tharshanna; Sajjad, Alia (Fall) Asgharian, Masoud; Sajjad, Alia (Winter) Kelome, Djivede (Summer)
Mathematics & Statistics (Sci) : Sampling distributions, point and interval estimation, hypothesis testing, analysis of variance, contingency tables, nonparametric inference, regression, Bayesian inference.
Terms: Fall 2022, Winter 2023
Instructors: Nadarajah, Tharshanna (Fall) Nadarajah, Tharshanna (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.
Computer Science (Sci) : Finite automata, regular languages, context-free languages, push-down automata, models of computation, computability theory, undecidability, reduction techniques.
Terms: Fall 2022, Winter 2023
Instructors: Panangaden, Prakash (Fall) Crépeau, Claude (Winter)
3 hours
Prerequisite: COMP 251.
Computer Science (Sci) : Advanced algorithm design and analysis. Linear programming, complexity and NP-completeness, advanced algorithmic techniques.
Terms: Fall 2022, Winter 2023
Instructors: Robere, Robert (Fall) Hatami, Hamed (Winter)
* Students may select either COMP 409 or ECSE 420, but not both.
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: This course is not scheduled for the 2022-2023 academic year.
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
Computer Science (Sci) : State-of-the-art language-based techniques for enforcing security policies in distributed computing environments. Static techniques (such as type- and proof-checking technology), verification of security policies and applications such as proof-carrying code, certifying compilers, and proof-carrying authentication.
Terms: This course is not scheduled for the 2022-2023 academic year.
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
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: Fall 2022
Instructors: Panangaden, Prakash (Fall)
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 2022-2023 academic year.
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
4 hours
Prerequisite: COMP 303.
Computer Science (Sci) : Model-driven software development; requirements engineering based on use cases and scenarios; object-oriented modelling using UML and OCL to establish complete and precise analysis and design documents; mapping to Java. Introduction to meta-modelling and model transformations, use of modelling tools.
Terms: This course is not scheduled for the 2022-2023 academic year.
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
Computer Science (Sci) : Conceptual foundations of information privacy: security and cryptography, privacy by design, privacy threats. Technical controls for supporting privacy: authorization, authentication, access control, malware and intrusion detection. Application-specific privacy concerns of databases, web and mobile applications, cloud storage.
Terms: Winter 2023
Instructors: Robillard, Martin (Winter)
Electrical Engineering : Techniques for eliciting requirements; languages and models for specification of requirements; analysis and validation techniques, including feature-based, goal-based, and scenario-based 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 2022
Instructors: Mussbacher, Gunter (Fall)
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 2022, Winter 2023
Instructors: Zilic, Zeljko (Fall) Giannacopoulos, Dennis (Winter)
(3-2-4)
Prerequisite: ECSE 427
Electrical Engineering : The course highlights human-computer interaction strategies from an engineering perspective. Topics include user interfaces, novel paradigms in human-computer interaction, affordances, ecological interface design, ubiquitous computing and computer-supported cooperative work. Attention will be paid to issues of safety, usability, and performance.
Terms: Fall 2022
Instructors: Cooperstock, Jeremy (Fall)
Electrical Engineering : Practical and theoretical knowledge for developing software languages and models; foundations for model-based software development; topics include principles of model-driven engineering; concern-driven development; intentional, structural, and behavioral models as well as configuration models; constraints; language engineering; domain-specific languages; metamodelling; model transformations; models of computation; model analyses; and modeling tools.
Terms: Winter 2023
Instructors: Mussbacher, Gunter (Winter)
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. Least-squares approximation. Iterative methods for solving a nonlinear equation. Discretization methods for integration and differential equations.
Terms: Fall 2022
Instructors: Chang, Xiao-Wen (Fall)
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. Multi-agent systems. Applications.
Terms: Fall 2022
Instructors: Dudek, Gregory L; Lotfi, Faraz (Fall)
Computer Science (Sci) : Database Design: conceptual design of databases (e.g., entity-relationship 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 2023
Instructors: Kemme, Bettina; Elsaadawy, Mona (Winter)
Computer Science (Sci) : Introduction to search methods. Knowledge representation using logic and probability. Planning and decision making under uncertainty. Introduction to machine learning.
Terms: Fall 2022
Instructors: Meger, David (Fall)
Computer Science (Sci) : Models and Architectures. Application-oriented communication paradigms (e.g. remote method invocation, group communication). Naming services. Synchronization (e.g. mutual exclusion, concurrency control). Fault-tolerance (e.g. process and replication, agreement protocols). Distributed file systems. Security. Examples of distributed systems (e.g. Web, CORBA). Advanced Topics.
Terms: Fall 2022
Instructors: Kemme, Bettina; D'silva, Joseph (Fall)
Computer Science (Sci) : The structure of a compiler. Lexical analysis. Parsing techniques. Syntax directed translation. Run-time implementation of various programming language constructs. Introduction to code generation for an idealized machine. Students will implement parts of a compiler.
Terms: Winter 2023
Instructors: Dubach, Christophe (Winter)
Computer Science (Sci) : Genre and history of games, basic game design, storytelling and narrative analysis, game engines, design of virtual worlds, real-time 2D graphics, game physics and physical simulation, pathfinding and game AI, content generation, 3D game concerns, multiplayer and distributed games, social issues.
Terms: This course is not scheduled for the 2022-2023 academic year.
Instructors: There are no professors associated with this course for the 2022-2023 academic year.
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, end-to-end protocols application of DNS, HTTP, P2P, fair queuing, performance modeling and analysis.
Terms: Winter 2023
Instructors: Liu, Xue (Winter)
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 2022, Winter 2023
Instructors: Li, Yue (Fall) Rabbany, Reihaneh (Winter)
Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent
Restriction(s): Not open to students who have taken or are taking COMP 451. Not open to students who have taken or are taking ECSE 551.
Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.
Computer Science (Sci) : Fundamental mathematical, algorithmic and representational issues in computer graphics: overview of graphics pipeline, homogeneous coordinates, projective transformations, line-drawing 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 2022
Instructors: Kry, Paul (Fall)
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 2022
Instructors: Siddiqi, Kaleem (Fall)
Computer Science (Sci) : Practical aspects of building software systems with machine learning components: requirements, design, delivery, quality assessment, and collaboration. Consideration of a user-centered mindset in development; integration of design and development considerations relevant to artificial intelligence, such as security, privacy, and fairness.
Terms: Fall 2022
Instructors: Guo, Jin (Fall)