Major Software Engineering (63 credits)

Offered by: Computer Science     Degree: Bachelor of Science

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 (39 credits)

* Students who have sufficient knowledge in a programming language do not need to take COMP 202.
** Students may select either COMP 310 or ECSE 427, but not both.

  • 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 2017, Winter 2018

    Instructors: David Becerra Romero, Giulia Alberini (Fall) Giulia Alberini, Bentley Oakes (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 2017, Winter 2018

    Instructors: Joseph P Vybihal (Fall) David Meger (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 2017, Winter 2018

    Instructors: Michael Langer (Fall) Jérôme Waldispuhl, Carlos Gonzalez Oliver (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 2017, Winter 2018

    Instructors: Hamed Hatami (Fall) Adrian Roshan Vetta (Winter)

    • 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 2017, Winter 2018

    Instructors: Kaleem Siddiqi (Fall) Joseph P Vybihal (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 2017, Winter 2018

    Instructors: Francisco Ferreira Ruiz, Brigitte Pientka (Fall) Clark Verbrugge (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 2017, Winter 2018

    Instructors: Martin Robillard (Fall) Joseph P Vybihal (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 2017, Winter 2018

    Instructors: Rola Harmouche (Fall) Rola Harmouche (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 2017

    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 2018

    Instructors: Matthias Schöttle (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 427 Operating Systems (3 credits) **

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

    Overview

    Electrical Engineering : Operating system services, file system organization, disk and cpu scheduling, virtual memory management, concurrent processing and distributed systems, protection and security. Aspects of the DOS and UNIX operating systems and the C programming language. Programs that communicate between workstations across a network.

    Terms: Fall 2017, Winter 2018

    Instructors: Rola Harmouche (Fall) Rola Harmouche (Winter)

  • 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 2017

    Instructors: Shane McIntosh (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 2017, Winter 2018

    Instructors: Bogdan Lucian Nica (Fall) Djivede Kelome (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 1 (3 credits)

    Offered by: Mathematics and Statistics (Faculty of Science)

    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 2017, Winter 2018

    Instructors: Philip Evan Decorte (Fall)

    • Fall

    • Corequisite: MATH 133.

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

Complementary Courses (24 credits)

At least 9 credits selected from groups A and B, with at least 3 credits selected from each:

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 2017, Winter 2018, Summer 2018

    Instructors: Stephen W Drury, Niko Laaksonen (Fall) Stephen W Drury (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 2017, Winter 2018, Summer 2018

    Instructors: David B Wolfson (Fall) Chien-Lin Su (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 2017, Winter 2018

    Instructors: Abbas Khalili Mahmoudabadi (Fall) Masoud Asgharian-Dastenaei (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:

At least 15 credits selected from the following, with at least 6 credits selected from Software Engineering Specializations, and at least 6 credits selected from Applications Specialties.

Software Engineering Specializations

* 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 2018

    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: Fall 2017

    Instructors: Brigitte Pientka (Fall)

  • 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 2017-2018 academic year.

    Instructors: There are no professors associated with this course for the 2017-2018 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 2017-2018 academic year.

    Instructors: There are no professors associated with this course for the 2017-2018 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: Fall 2017

    Instructors: Jorg Andreas Kienzle (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 2017

    Instructors: Dennis Giannacopoulos (Fall)

  • 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: Fall 2017

    Instructors: Gunter Mussbacher (Fall)

Application Specialties

* Students may select either COMP 557 or ECSE 532, but not both.

  • 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 2017

    Instructors: Xiao-Wen Chang (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 2017

    Instructors: Gregory L Dudek (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 2018

    Instructors: Joseph D'silva (Winter)

  • 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 2018

    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: Fall 2017

    Instructors: Bettina Kemme, Omar Asad (Fall)

  • 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 2018

    Instructors: Alexander Krolik (Winter)

  • 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 2017

    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 2017-2018 academic year.

    Instructors: There are no professors associated with this course for the 2017-2018 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 2018

    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 2017, Winter 2018

    Instructors: Joelle Pineau (Fall) Sarath Chandar, Ryan Lowe, Herke Van Hoof (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: Winter 2018

    Instructors: Paul Kry (Winter)

  • COMP 558 Fundamentals of Computer Vision (3 credits)

    Offered by: Computer Science (Faculty of Science)

    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 2017

    Instructors: Kaleem Siddiqi (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 2017

    Instructors: Jeremy Cooperstock (Fall)

  • ECSE 532 Computer Graphics (3 credits) *

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

    Overview

    Electrical Engineering : Introduction to computer graphics systems and display devices: raster scan, scan conversion, graphical input and interactive techniques - window environments; display files: graphics languages and data structures: 2D transformations; 3D computer graphics, hidden line removal and shading; graphics system design; applications. Laboratory project involving the preparation and running of graphics programs.

    Terms: This course is not scheduled for the 2017-2018 academic year.

    Instructors: There are no professors associated with this course for the 2017-2018 academic year.

Faculty of Science—2017-2018 (last updated Aug. 23, 2017) (disclaimer)