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Major Concentration Software Engineering (37 credits)

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Note: This is the 2017–2018 eCalendar. Update the year in your browser's URL bar for the most recent version of this page, or .

Offered by: Computer Science     Degree: Bachelor of Arts and Science

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."

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)

* Students who have sufficient knowledge in a programming language do not need to take COMP 202 and can replace it with additional computer science complementary course credits.

  • 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, Summer 2018

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

    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: Vybihal, Joseph P (Fall) Meger, David (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: Langer, Michael (Fall) Gonzalez Oliver, Carlos; Waldispuhl, Jérôme (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: Hatami, Hamed (Fall) Vetta, Adrian Roshan (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: Siddiqi, Kaleem (Fall) Vybihal, Joseph P (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: Ferreira Ruiz, Francisco; Pientka, Brigitte (Fall) Verbrugge, Clark (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: Robillard, Martin (Fall) Vybihal, Joseph P (Winter)

  • 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: D'silva, Joseph (Winter)

  • 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: Nica, Bogdan Lucian (Fall) Kelome, Djivede (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: Decorte, Philip Evan (Fall) Seamone, Benjamin (Winter)

    • 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 (7 credits)

6-7 credits from:

  • COMP 322 Introduction to C++ (1 credit)

    Offered by: Computer Science (Faculty of Science)

    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 2018

    Instructors: Zammar, Chad (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: Kienzle, Jorg Andreas (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: Schöttle, Matthias; 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)

    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: Kienzle, Jorg Andreas (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: Mussbacher, Gunter (Fall)

or any computer science course at the 300 level or above, excluding COMP 364 and COMP 396.

Bachelor of Arts & Science—2017-2018 (last updated Oct. 12, 2017) (disclaimer)
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