In accordance with Senate's *Policy Regarding Inactive Courses*,
courses which have not been offered in the previous three academic years and
which are not scheduled to be offered in the current academic year have been
removed from the following listing. For information about any of these inactive
courses, please contact the Head of the Department.

**FIRST YEAR COURSES**

**1600. Basic Computing and Information Technology (F) & (W).**
This course offers an overview of computers and information technology. It
provides students with the knowledge necessary to answer questions, such as:
What is a computer system? How does it work? How is it used? This is done
through the use of popular spreadsheet, word processing and database software
packages and the Internet. Social issues and implications will also be included.

Prerequisite: Level III Advanced Mathematics or Mathematics 1090, which
can be taken concurrently.

Lectures: Three hours per week.

Laboratory: Three hours per week.

*NOTE: Students can receive credit for only one of Computer Science 1600,
Computer Science 2650 or Computer Science 2801.*

**1700. Introduction to Computer Science (F) & (W).**
This course lays the foundation for the art and the science of computing.
The course contains fundamental and topical issues in computers, languages,
programming and applications. This course is required of all Computer Science
majors but is also available to non-majors.

Prerequisite: Mathematics 1090 or Level III Advanced Mathematics or equivalent.

Lectures: Three hours per week.

Laboratory: Three hours per week.

*NOTE: Students who have previously completed Computer Science 2700 will
not be permitted to register or receive credit for Computer Science 1700.*

**SECOND YEAR COURSES**

**2602. Computer Programming in FORTRAN (F) & (W).** Introduction
to computers and their use; and the FORTRAN programming language and its application
to the computer solution of numeric and non-numeric problems.

Prerequisite: Mathematics 1000.

*NOTE: Students who have received credit for the former Computer Science
2600, or the former 2601, or the former 2800 cannot receive credit for Computer
Science 2602.*

**2650. Introduction to Computing and Information Technology (F) &
(W). **This course provides a broad overview of hardware and software components
of computer systems, their structure, and principles of operation. The topics
include algorithmic problem solving, visual programming, operating system
services, computer networks, elements of artificial intelligence and societal
issues. In addition to three one-hour lectures, there will be three hours
per week of structured laboratory sessions. Internet and microcomputer software
tools in the Windows environment are introduced.

Prerequisite: Level III Advanced Mathematics or Mathematics 1090.

*NOTE: Students can receive credit for only one of Computer Science 1600,
Computer Science 2650 or Computer Science 2801.*

**2710. Problem Solving and Programming (F) & (W).** This
course emphasizes algorithmic problem solving and sound programming techniques;
for instance, mathematical models for abstract data types are formally defined
and their relevant properties are proved. Basic techniques for the organization
of data in the computer's storage are discussed and the basics for proving
properties of programs are given.

Lectures: Three hours per week.

Laboratory: Three hours per week.

Prerequisite: Computer Science 1700.

**2711. Introduction to Algorithms and Data Structures (F) &
(W).** This course includes the study of standard ways of organizing
and manipulating data in the computer's storage. Fundamental concepts in the
design and analysis of algorithms are also discussed.

Lectures: Three hours per week.

Laboratory: Three hours per week.

Prerequisite: Computer Science 2710.

*NOTE: It is recommended that students complete Computer Science
2740 prior to registering for Computer Science 2711.*

**2740. Discrete Structures I (F) & (W).** Basic concepts
of logic. Propositional logic and its proof system. The language of predicate
logic. Sets, functions and relations, induction and recursion. Basics of graph
theory, elementary properties of graphs.

Prerequisite: Computer Science 1700.

NOTE: Credit cannot be obtained for both Computer Science 2740 and Pure
Mathematics 2320.

**2741. Discrete Structures II (F) & (W).** A follow-up
of Computer Science 2740 dealing with more advanced topics in Discrete Mathematics.
These topics include: classical graph theoretic problems, operations, algebras,
abstract algebraic constructions, more on set theory and predicate logic.

Prerequisite: Computer Science 2710 and 2740.

*NOTE: Credit cannot be obtained for both Computer Science 2741 and Applied
Mathematics/Pure Mathematics 3240.
*

**2801. Introductory Computing for Business (F) & (W). **This course
introduces students to computer applications in business, document processing,
application development, decision support, and information management. A three
hour laboratory is required.

Prerequisite: Level III Advanced Mathematics or Mathematics 1090.

*NOTE: Students can receive credit for only one of Computer Science 1600,
Computer Science 2650 or Computer Science 2801.*

**THIRD YEAR COURSES**

**3700. Industrial Experience (F) & (W).** Students who are admitted
to CIIO are required to register for this non-credit course every semester
during their internship. This course is open only to students who have been
accepted into the Internship Program and provides an opportunity for qualified
students to obtain rewarding job experience of 8, 12 or 16 months of continuous
duration, during the course of their studies.

Prerequisite: Admission to the Computer Industry Internship Option (CIIO).

**3710. Vocational Languages (W).** Study of several programming languages
of vocational significance (e.g. a selection from C, C++, Prolog, Perl, Python
and LISP). The use of appropriate programming paradigms to solve some significant
problems.

Prerequisite: Computer Science 2711.

**3711. Algorithms and Complexity (F) & (W).** This course
introduces the most common and effective algorithm design techniques (e.g.
divide and conquer, dynamic programming, greedy algorithms). The theory of
NP - completeness is also discussed. Examples will be drawn from various fields
such as graph theory and string matching.

Prerequisite: Computer Science 2711 and 2741.

**3714. Programming Languages and their Processors (F) & (W).**
This course reviews typical elements of (imperative) programming languages,
and then discusses language implementations in the form of compilers and interpreters.
The topics include specification of syntax and semantics of programming languages,
discussion of expressions and assignments, side effects, control structures,
data and procedural abstractions, parameter passing mechanisms, bindings,
scopes, and type systems. The recursive-descent technique is used for illustrations
of different aspects of syntax analysis, code generation and error recovery.
Language interpreters are discussed for both low-level and high-level languages.

Prerequisites: Computer Science 3740 and 3724.

**3718. Programming in the Small (F).** The main objective
of this course is to demonstrate the tools and techniques used in the construction
of small software systems. The software tools and techniques to be covered
include analysis and design of software components, software construction
tools (e.g. linkers, builders, debuggers), software library use and design,
and system integration.

Prerequisite: CS 2711 and CS 2741.

**3724. Computer Organization (F) & (W).** This course
begins with elementary logic elements and progresses through boolean algebra,
synthesis and analysis of combinational and sequential circuits, finally covering
aspects of von Newmann machine organization. It deals with topics such as
number systems, coding, arithmetic/logic units, register transfer languages,
algorithmic state machines, PLA, Mux, One Hot implementations, microprogramming,
memory, instruction processing cycle, etc.

Prerequisite: Computer Science 2711 and 2741.

**3725. Computer Architecture (F) & (W).** Using the background
offered in Computer Science 3724, this course covers advanced topics in the
areas of memory system organizations (eg. overlapping, interleaving, cache,
associative memory, virtual memory, etc.), foundations of high-speed computations
(eg. various types of dependencies, pipelining, co-operations and contentions,
synchronizations, etc.), interfacing and communications, and alternative
architectures (eg. RISC/CICS, VLIW, superscalar, systolic, etc.)

Prerequisite: Computer Science 3724.

**3731 Numerical Methods (W). **The development of algorithms for the
numerical solution of mathematical problems and the study of the numerical
stability of these algorithms are the main objectives of this course. The
efficiency of these algorithms with respect to speed and storage requirements
is considered as well. Emphasis is also placed on the study of the sensitivity
of selected problems to perturbations in the data. There is also a brief introduction
to the development of numerical algorithms that take advantage of advanced
computer architectures, such as pipeline processors, array processors and
parallel processors.

Prerequisites: Mathematics 2000, and one Computer Science 2602 or 2710.

*NOTE: Credit cannot be obtained for both Computer Science 3731 and Applied
Mathematics 3132.*

**3740. Abstract Machines, Languages and Computations (F) & (W).**
This course provides an introduction to formal languages, formal grammars
and computations. The topics include regular languages, regular expressions,
deterministic and nondeterministic finite automata, formal grammars, Chomsky
hierarchy, context-free grammars and languages, ambiguity, pushdown automata,
Turing machines, recursive and recursively enumerable languages, Church-Turing
thesis, and the concept of algorithm, universal Turing machines, decidability,
reducibility.

Prerequisite: Computer Science 2711 and 2741.

**3753. Computational Aspects of Linear Programming (F).** An introduction
to the Linear Programming Problem (LPP). The emphasis is placed upon developing
the most recent and numerically reliable algorithms for the solution of the
Linear Programming Problem. The numerical stability of these algorithms will
be examined as well. Geometric understanding of the LPP. Simplex method for
the LPP. Sparse matrix LPP. Duality and postoptimality analysis. Extensions
to the simplex algorithm. Principles of interior algorithms for the LPP.

Prerequisite: Mathematics 2050, and one of Computer Science 2602 or 2710.

**FOURTH YEAR COURSES**

**4711. Structure of Programming Languages (F).** Programming
language design considerations; syntactic and semantic structure; survey of
typical features and operations; analysis of facilities for control and data
structuring; language extensibility; execution models; formal specification
of programming languages.

Prerequisite: Computer Science 3714.

**4712. Compiler Construction (W).** Properties of formal
grammars and languages; syntax-directed parsing and code generation; top-down
and bottom-up parsing methods; LL(k) and LR(k) grammars and parsers; Code
optimization; compiler writing tools.

Prerequisite: Computer Science 3714.

**4715 and 4717. Special Topics in Programming Languages.**

**4716. Software System Design and Implementation (W).** This
course studies the methodology of developing well-engineered large-scale software
systems. It introduces the principal paradigms of software design and implementation
and provides hands-on practice of software engineering concepts and object-oriented
techniques (with CASE tools) in project team environments.

Prerequisite: Computer Science 4718.

**4718. Software Methodology (F) & (W).** This course
introduces methods and tools for developing, managing, and maintaining large-scale
software systems. The life-cycle of software development is covered with special
emphasis. The topics discussed include development models and environments,
project management, requirement engineering, design and programming techniques,
software validation, maintenance, and re-engineering.

Prerequisites: Computer Science 3711. Students are encouraged to take Computer
Science 3718 prior to doing this course.

**4719. Software Specification (F).** The primary emphasis
in this course is on the mathematical specification of software in Z. Z is
a mathematical notation based on sets, functions, and relations, using schemas
to place logical constraints on sets of values. The basic of Z notation and
schema calculus will be presented, followed by examples of the use of Z. In
addition, some elementary features of a pure functional programming language
will be presented to further support the advantages of a mathematical treatment
of software.

Prerequisite: Computer Science 3711.

**4721. Operating Systems Principles (F) & (W).** This
course provides an introduction to the main concepts and techniques used
in operating systems. The topics include history of operating systems, structures
of operating systems, process management, process coordination, deadlocks,
memory management, secondary storage management, file management, security
and protection issues, elements of distributed operating systems, and selected
case studies.

Prerequisite: Computer Science 3725.

**4723. Introduction to Microprocessors (F).** The architecture
and instruction sets for several microprocessors are examined. The use of
microprocessors as device controllers; comparisons of hardware and programed
techniques; microprocessor interfacing with external devices; methods of I/O;
bus structures; modern microprocessor support devices are discussed.

Prerequisite: Computer Science 3724.

Lecture: Three hours per week.

Laboratory: Minimum of three hours per week. Practical experience with basic
principles will be obtained through laboratory experience.

**4726-4729. Special Topics in Computer Systems.**

**4734. Matrix Computations and Applications (W).** An introduction
to linear algebra; solution to linear systems; scaling, improving and estimating
accuracy; the linear least squares problem; the eigenvalue problem; singular
value decomposition of a matrix; the generalized eigenvalue problem.

Prerequisite: Computer Science 3731.

**4736-4739. Special Topics in Numerical Computations.**

**4741. Theory of Abstract Automata and Formal Languages (W).**
This course covers more advanced topics of abstract automata, formal grammars
and languages. They include timed and stochastic automata, probabilistic grammars,
tree automata and languages, cellular automata, matrix grammars, controlled
rewriting systems, and L-systems. Applications in computer graphics, visualization
and digital images, and modeling of systems are used as illustrations of
the formalisms.

Prerequisite: Computer Science 3740.

**4742. Computational Complexity (F).** This course is an
in-depth discussion of computational complexity theory. Topics covered in
the course include: models of computation (for both serial and parallel computations);
complexity measures; reducibility; complexity classes (NP, PSPACE, NC, LOGSPACE
and P); and randomized computations.

Prerequisite: Computer Science 3711 and 3740.

**4745-4749 (excluding 4748). Special Topics in Theoretical Aspects.**

Prerequisite: Consent of Head of Department.

**4751. Computer Graphics (F).** Display devices, display
processors, display file compilers, display transformations, structured display
files, graphical input devices, perspective, hidden line elimination, languages
and graphics systems.

In addition to three one-hour lectures, there will be a minimum three hour
laboratory per week, to be scheduled by the Department.

Prerequisite: Computer Science 3711 and Mathematics 2050.

**4753. Introduction to Artificial Intelligence (F).** Selected topics
from AI programming languages; problem solving; search and heuristic search;
game-playing; knowledge-based systems; pattern recognition; computer vision;
natural language understanding; and machine learning.

Prerequisite: Computer Science 3711.

**4754. Data Base Systems (F).** Data Base as a new approach
to data processing; survey of 3 different types of data base systems: relational,
hierarchical and network; security and integrity; comparison studies of some
existing systems.

Prerequisite: Computer Science 3725.

**4755-4769 (excluding 4756, 4759, 4761 and 4762). Special Topics
in Applications.**

**4756. Image Processing (W).** Lectures will centre on the
key analytical and algorithmic tools and concepts of digital image processing.
Topics will include Transformations, Enhancement, Encoding, Data Bases, Segmentation
and Description.

In addition to three one-hour lectures, there will be a three hour laboratory
per week, to be scheduled by the Department.

Prerequisite: Computer Science 3711.

**4759. Computer Networks (W). **The operation of computer
networks requires the following: a) communication between two computers, b)
information transfer between two computers not directly connected, and c)
services that need computer communication. This course focuses on the standard
solutions and services used to fulfill the previous requirements. These include:
physical transmission of signals, reliable communication based on unreliable
communication channels, the routing of messages between connected computers
to reach computers that are not directly connected, e-mail, file transfer,
name servers, remote terminal access and the World Wide Web. Particular attention
will be placed on the workings of the Internet.

Prerequisite: Computer Science 3725.

**4761. Human-Computer Interaction (W).** User modelling,
task analysis, user-interface design, environments and toolkits, prototyping,
user psychology, empirical methods, usability analysis. Representative methods,
techniques, and tools are applied to the design and development of human-computer
systems.

Prerequisites: Computer Science 3714 and Statistics 2510*.

**4780. Honours Project. **This course introduces computer science honours
students to research activities, familiarizes them with a special problem
in computer science, and provides independent study on an advanced topic
under the direct supervision of a member of the computer science faculty.
The topic is decided in consultation with the supervisor. The student is required
to produce a written report on the project, to include the literature search
on the topic, and to present this work at a departmental seminar prior to
the last week of the semester.

Prerequisite: Consent of the Head of Department.

*NOTE: This course is only available to students who have been accepted
into the honours program.*

** Inactive Course*

Last modified on June 4, 2003 by R. Bruce

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