Note: This is the 2018–2019 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .
Program Requirements
The Major Concentration Software Engineering focuses on the techniques and methodology required to design and develop complex software systems and covers the subject commonly known as "Software Engineering". Arts students that are interested in further study in Computer Science can combine the Major Concentration in Software Engineering with the Supplementary Minor Concentration in Computer Science. For further information, please consult the Program Adviser.
Students with two programs in the same department/unit must have a third program in a different department/unit to be eligible to graduate. Please refer to the Faculty of Arts regulations for "Faculty Degree Requirements", "About Program Requirements", and "Departmental Programs" for the Multi-track System options.
MATH 133, MATH 140, and MATH 141 (or their equivalents) must be completed prior to taking courses in this program.
Note: This program does not lead to certification as a Professional Engineer.
Required Courses (30 credits)
* Note: Students who have sufficient knowledge in a programming language do not need to take COMP 202 but can replace it with an additional Computer Science complementary course.
-
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: Alberini, Giulia; Vybihal, Joseph P (Fall) Alberini, Giulia; Yu, Tzu-Yang; Zammar, Chad (Winter) Yu, Tzu-Yang (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: Meger, David (Fall) Vybihal, Joseph P; Zammar, Chad (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 non-recursive algorithms (searching and sorting, tree and graph traversal). Abstract data types, inheritance. Selected topics.
Terms: Fall 2018, Winter 2019
Instructors: Langer, Michael; Alberini, Giulia (Fall) Robillard, Martin; Alberini, Giulia (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: Waldispuhl, Jérôme (Fall) Devroye, Luc P; McLeish, Erin Leigh (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: Kry, Paul (Fall) Siddiqi, Kaleem (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: Pientka, Brigitte (Fall) Panangaden, Prakash (Winter)
3 hours
Prerequisite: COMP 250
-
COMP 303 Software Design (3 credits)
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 2018, Winter 2019
Instructors: Nassif, Mathieu; Vybihal, Joseph P (Fall) Guo, Jin (Winter)
-
COMP 421 Database Systems (3 credits)
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 2019
Instructors: D'silva, Joseph (Winter)
-
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: Kelome, Djivede (Fall) Macdonald, Jeremy (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: Macdonald, Jeremy; Nica, Bogdan (Fall) Macdonald, Jeremy; Pequignot, Yann Batiste (Winter)
Complementary Courses (6 credits)
At least 6 credits from:
-
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 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 2018
Instructors: Mussbacher, Gunter (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 2018
Instructors: McIntosh, Shane (Fall)
-
ECSE 539 Advanced Software Language Engineering (4 credits)
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 2018
Instructors: Mussbacher, Gunter (Fall)
or any COMP courses at the 300 level or above, excluding COMP 364 and COMP 396.
Suggested COMP courses are:
-
COMP 322 Introduction to C++ (1 credit)
Overview
Computer Science (Sci) : Basics and advanced features of the C++ language. Syntax, memory management, class structure, method and operator overloading, multiple inheritance, access control, stream I/O, templates, exception handling.
Terms: Winter 2019
Instructors: Zammar, Chad (Winter)
-
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: Kienzle, Jorg Andreas (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: Kienzle, Jorg Andreas (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 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: Robillard, Martin (Winter)
4 hours
Prerequisite: COMP 303.
-
COMP 533 Model-Driven Software Development (3 credits)
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 2018
Instructors: Kienzle, Jorg Andreas (Fall)