Honours Software Engineering (75 credits)

Offered by: Computer Science     Degree: Bachelor of Science

Program Requirements

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.

Required Courses

39-42 credits

* Students who have sufficient knowledge in a programming language do not need to take COMP 202.

  • COMP 202 Foundations of Programming (3 credits) *

    Offered by: Computer Science (Faculty of Science)

    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)

    Offered by: Computer Science (Faculty of Science)

    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)

    Offered by: Computer Science (Faculty of Science)

    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 non-recursive 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)

    • 3 hours

    • Prerequisites: Familiarity with a high level programming language and CEGEP level Math.

    • Students with limited programming experience should take COMP 202 or equivalent before COMP 250. See COMP 202 Course Description for a list of topics.

  • COMP 251 Algorithms and Data Structures (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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

    • Corequisite(s): MATH 235 or MATH 240 or MATH 363.

    • 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)

    Offered by: Computer Science (Faculty of Science)

    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)

  • COMP 302 Programming Languages and Paradigms (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

  • COMP 303 Software Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2019, Winter 2020

    Instructors: Martin Robillard (Fall) Jin Guo (Winter)

  • COMP 310 Operating Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

  • COMP 361D1 Software Engineering Project (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

  • COMP 361D2 Software Engineering Project (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

    Offered by: Computer Science (Faculty of Science)

    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 non-Honours students with permission of the department.

  • ECSE 429 Software Validation (3 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    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)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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)

    • Fall and Winter

    • Prerequisite: MATH 133 or equivalent

    • Restriction: Not open to students in Mathematics programs nor to students who have taken or are taking MATH 236, MATH 247 or MATH 251. It is open to students in Faculty Programs

  • MATH 240 Discrete Structures (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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)

    • Fall and Winter

    • Corequisite: MATH 133.

    • Restriction: For students in any Computer Science, Computer Engineering, or Software Engineering programs. Others only with the instructor's permission. Not open to students who have taken or are taking MATH 235.

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)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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)

    • Prerequisites: MATH 141 or equivalent.

    • Restriction: Intended for students in Science, Engineering and related disciplines, who have had differential and integral calculus

    • Restriction: Not open to students who have taken or are taking MATH 356

  • MATH 324 Statistics (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 Asgharian-Dastenaei (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)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Finite automata, regular languages, context-free languages, push-down automata, models of computation, computability theory, undecidability, reduction techniques.

    Terms: Fall 2019

    Instructors: Claude Crepeau (Fall)

  • COMP 360 Algorithm Design (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Advanced algorithm design and analysis. Linear programming, complexity and NP-completeness, 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) *

    Offered by: Computer Science (Faculty of Science)

    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 Language-based Security (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 525 Formal Verification (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 529 Software Architecture (4 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 533 Model-Driven Software Development (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • ECSE 326 Software Requirements Engineering (3 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    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 2019

    Instructors: Shane McIntosh (Fall)

  • ECSE 420 Parallel Computing (3 credits) *

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    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)

  • ECSE 424 Human-Computer Interaction (3 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    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 2019

    Instructors: Jeremy Cooperstock (Fall)

  • ECSE 437 Software Delivery (3 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    Electrical Engineering : Design, development, and implementation of code integration processes, release pipelines, and deployment strategies.

    Terms: Fall 2019

    Instructors: Shane McIntosh (Fall)

    • (3-2-4)

    • Prerequisite(s): ECSE 321 or COMP 303

    • Restrictions: Restricted to students majoring in Software Engineering.

  • ECSE 539 Advanced Software Language Engineering (4 credits)

    Offered by: Electrical & Computer Engr (Faculty of Engineering)

    Overview

    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: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

Group D: Applications

  • COMP 350 Numerical Computing (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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. Least-squares 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)

    Offered by: Computer Science (Faculty of Science)

    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. Multi-agent systems. Applications.

    Terms: Fall 2019

    Instructors: David Meger (Fall)

  • COMP 421 Database Systems (3 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2020

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 424 Artificial Intelligence (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 520 Compiler Design (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2020

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 521 Modern Computer Games (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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: Fall 2019

    Instructors: Clark Verbrugge (Fall)

  • COMP 522 Modelling and Simulation (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    Computer Science (Sci) : Simulation and modelling processes, state automata, Petri Nets, state charts, discrete event systems, continuous-time models, hybrid models, system dynamics and object-oriented modelling.

    Terms: This course is not scheduled for the 2019-2020 academic year.

    Instructors: There are no professors associated with this course for the 2019-2020 academic year.

  • COMP 535 Computer Networks 1 (4 credits)

    Offered by: Computer Science (Faculty of Science)

    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, end-to-end 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)

    Offered by: Computer Science (Faculty of Science)

    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)

    • Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent

    • Restriction(s): Not open to students who have taken COMP 598 when topic was "Applied Machine Learning"

    • Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.

  • COMP 557 Fundamentals of Computer Graphics (4 credits)

    Offered by: Computer Science (Faculty of Science)

    Overview

    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 2019

    Instructors: Paul Kry (Fall)

  • COMP 558 Fundamentals of Computer Vision (4 credits)

    Offered by: Computer Science (Faculty of Science)

    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)

Faculty of Science—2019-2020 (last updated Aug. 20, 2019) (disclaimer)