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Department of Mathematics  Faculty of Science Simon Fraser University Calendar  Spring 2021
Mathematics and Computing Science Joint Honours
This program is offered cooperatively by the Department of Mathematics and the School of Computing Science. In general, students are expected to meet the requirements of both the department and the school with respect to admission, continuation and graduation requirements.
Prerequisite Grade Requirement
To enroll in a course offered by the Department of Mathematics, a student must obtain a grade of C or better in each prerequisite course. Some courses may require higher prerequisite grades. Check the MATH course’s Calendar description for details.
Students will not normally be permitted to enroll in any course for which a D grade or lower was obtained in any prerequisite. No student may complete, for further credit, any course offered by the Department of Mathematics which is a prerequisite for a course the student has already completed with a grade of C or higher, without permission of the department.
Computing science course entry requires a grade of C or better in each prerequisite course. A minimum 2.40 CGPA is required for 200, 300 and 400 division computing courses.
Program Requirements
The program is subject to Faculty of Science and University regulations. Course and prerequisite admission is subject to departmental requirements.
Faculty of Applied Sciences residency requirements apply to the computing science courses used toward the program.
Students complete at least 120 units of which at least 60 units are at the upper division level as specified below.
Lower Division Requirements
Students complete at least 4347 units, including all three of
An elementary introduction to computing science and computer programming, suitable for students with little or no programming background. Students will learn fundamental concepts and terminology of computing science, acquire elementary skills for programming in a highlevel language and be exposed to diverse fields within, and applications of computing science. Topics will include: pseudocode, data types and control structures, fundamental algorithms, computability and complexity, computer architecture, and history of computing science. Treatment is informal and programming is presented as a problemsolving tool. Prerequisite: BC Math 12 or equivalent is recommended. Students with credit for CMPT 102, 128, 130 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129, 130 or 135 first may not then take this course for further credit. Quantitative/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Angelica Lim 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Angelica Lim 
Mo, We, Fr 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 
D400 
Harinder Khangura 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D401 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D402 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D403 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D404 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D405 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D406 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D407 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D408 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
A rigorous introduction to computing science and computer programming, suitable for students who already have some background in computing science and programming. Intended for students who will major in computing science or a related program. Topics include: fundamental algorithms; elements of empirical and theoretical algorithmics; abstract data types and elementary data structures; basic objectoriented programming and software design; computation and computability; specification and program correctness; and history of computing science. Prerequisite: CMPT 120. Corequisite: CMPT 127. Students with credit for CMPT 126, 129, 135 or CMPT 200 or higher may not take for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Victor Cheung 
Mo 2:30 PM – 4:20 PM We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
Builds on CMPT 120 to give a handson introduction to programming in C and C++, the basics of program design, essential algorithms and data structures. Guided labs teach the standard tools and students exploit these ideas to create software that works. To be taken in parallel with CMPT 125. Prerequisite: CMPT 120 or CMPT 128 or CMPT 130. Corequisite: CMPT 125.
Section  Instructor  Day/Time  Location 

D100 
Anne Lavergne 
Tu 8:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Anne Lavergne 
Tu 11:30 AM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D300 
Anne Lavergne 
Tu 2:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
or both of
An introduction to computing science and computer programming, using a systems oriented language, such as C or C++. This course introduces basic computing science concepts. Topics will include: elementary data types, control structures, functions, arrays and strings, fundamental algorithms, computer organization and memory management. Prerequisite: BC Math 12 (or equivalent, or any of MATH 100, 150, 151, 154, or 157). Students with credit for CMPT 102, 120, 128 or 166 may not take this course for further credit. Students who have taken CMPT 125, 129 or 135 first may not then take this course for further credit. Quantitative/BreadthScience.
A second course in systemsoriented programming and computing science that builds upon the foundation set in CMPT 130 using a systemsoriented language such as C or C++. Topics: a review of the basic elements of programming; introduction to objectoriented programming (OOP); techniques for designing and testing programs; use and implementation of elementary data structures and algorithms; introduction to embedded systems programming. Prerequisite: CMPT 130. Students with credit for CMPT 125, 126, or 129 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Toby Donaldson 
Mo, We, Fr 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D105 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D106 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D108 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
and all of
Introduction to a variety of practical and important data structures and methods for implementation and for experimental and analytical evaluation. Topics include: stacks, queues and lists; search trees; hash tables and algorithms; efficient sorting; objectoriented programming; time and space efficiency analysis; and experimental evaluation. Prerequisite: (MACM 101 and ((CMPT 125 and 127), CMPT 129 or CMPT 135)) or (ENSC 251 and ENSC 252). Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Igor Shinkar 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D102 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D103 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D104 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D105 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D106 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D107 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D108 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D200 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D201 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D202 
We 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D203 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D204 
We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 

D205 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D206 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D207 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D208 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
An overview of various techniques used for software development and software project management. Major tasks and phases in modern software development, including requirements, analysis, documentation, design, implementation, testing,and maintenance. Project management issues are also introduced. Students complete a team project using an iterative development process. Prerequisite: One W course, CMPT 225, (MACM 101 or (ENSC 251 and ENSC 252)) and (MATH 151 or MATH 150). MATH 154 or MATH 157 with at least a B+ may be substituted for MATH 151 or MATH 150. Students with credit for CMPT 275 may not take this course for further credit.
Section  Instructor  Day/Time  Location 

D100 
Saba Alimadadi Jani 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Steve Pearce 
Mo, We, Fr 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
E100 
We 5:30 PM – 8:20 PM 
REMOTE LEARNING, Burnaby 
The curriculum introduces students to topics in computer architecture that are considered fundamental to an understanding of the digital systems underpinnings of computer systems. Prerequisite: Either (MACM 101 and ((CMPT 125 and CMPT 127) or CMPT 135)) or (MATH 151 and CMPT 102 for students in an Applied Physics program).
Section  Instructor  Day/Time  Location 

D100 
Anne Lavergne 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D101 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D102 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D103 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D104 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D105 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D106 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

D108 
Th 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
Introduction to counting, induction, automata theory, formal reasoning, modular arithmetic. Prerequisite: BC Math 12 (or equivalent), or any of MATH 100, 150, 151, 154, 157. Quantitative/BreadthScience.
Section  Instructor  Day/Time  Location 

D100 
Andrei Bulatov 
Mo, We, Fr 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
D101 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D105 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D106 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 

D108 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 

D200 
Harinder Khangura 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D201 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D202 
Th 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 

D203 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D204 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D205 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D206 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D207 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D208 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 
A continuation of MACM 101. Topics covered include graph theory, trees, inclusionexclusion, generating functions, recurrence relations, and optimization and matching. Prerequisite: MACM 101 or (ENSC 251 and one of MATH 232 or MATH 240). Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Michael Monagan 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Mahsa Faizrahnemoon 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D300 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

OP01  TBD  
OP02  TBD  
OP03  TBD 
Using a mathematical software package for doing calculations in linear algebra. Development of computer models that analyze and illustrate applications of linear algebra. All calculations and experiments will be done in the Matlab software package. Topics include: largescale matrix calculations, experiments with cellular automata, indexing, searching and ranking pages on the internet, population models, data fitting and optimization, image analysis, and cryptography. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and one of MATH 150, 151, 154 or 157 and one of MATH 232 or 240. MATH 232 or 240 can be taken as corequisite. Students in excess of 80 units may not take MACM 203 for further credit. Quantitative.
Using a mathematical software package for doing computations from calculus. Development of computer models that analyze and illustrate applications of calculus. All calculations and experiments will be done in the Maple software package. Topics include: graphing functions and data, preparing visual aids for illustrating mathematical concepts, integration, Taylor series, numerical approximation methods, 3D visualization of curves and surfaces, multidimensional optimization, differential equations and disease spread models. Prerequisite: One of CMPT 102, 120, 126, 128 or 130 and MATH 251. MATH 251 can be taken as a corequisite. Students in excess of 80 units may not take MACM 204 for further credit. Quantitative.
Mathematical induction. Limits of real sequences and real functions. Continuity and its consequences. The mean value theorem. The fundamental theorem of calculus. Series. Prerequisite: MATH 152; or MATH 155 or 158 with a grade of B. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Stephen Choi 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Th 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Th 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
Rectangular, cylindrical and spherical coordinates. Vectors, lines, planes, cylinders, quadric surfaces. Vector functions, curves, motion in space. Differential and integral calculus of several variables. Vector fields, line integrals, fundamental theorem for line integrals, Green's theorem. Prerequisite: MATH 152; or MATH 155 or MATH 158 with a grade of at least B. Recommended: It is recommended that MATH 240 or 232 be taken before or concurrently with MATH 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jamie Mulholland 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
Basic laws of probability, sample distributions. Introduction to statistical inference and applications. Prerequisite: or Corequisite: MATH 152 or 155 or 158. Students wishing an intuitive appreciation of a broad range of statistical strategies may wish to take STAT 100 first. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Derek Bingham 
Mo, We, Fr 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
and one of
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Topics as for Math 151 with a more extensive review of functions, their properties and their graphs. Recommended for students with no previous knowledge of Calculus. In addition to regularly scheduled lectures, students enrolled in this course are encouraged to come for assistance to the Calculus Workshop (Burnaby), or Math Open Lab (Surrey). Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B+, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 151, 154 or 157 may not take MATH 150 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Sophie Burrill 
Mo, Tu, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Natalia Kouzniak 
Mo, We, Fr 11:30 AM – 12:20 PM We 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD  
OP03  TBD 
Designed for students specializing in mathematics, physics, chemistry, computing science and engineering. Logarithmic and exponential functions, trigonometric functions, inverse functions. Limits, continuity, and derivatives. Techniques of differentiation, including logarithmic and implicit differentiation. The Mean Value Theorem. Applications of differentiation including extrema, curve sketching, Newton's method. Introduction to modeling with differential equations. Polar coordinates, parametric curves. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least A, or MATH 100 with a grade of at least B, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 154 or 157 may not take MATH 151 for further credit. Quantitative.
Designed for students specializing in the biological and medical sciences. Topics include: limits, growth rate and the derivative; elementary functions, optimization and approximation methods, and their applications; mathematical models of biological processes. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 157 may not take MATH 154 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Luis Goddyn 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Designed for students specializing in business or the social sciences. Topics include: limits, growth rate and the derivative; logarithmic, exponential and trigonometric functions and their application to business, economics, optimization and approximation methods; introduction to functions of several variables with emphasis on partial derivatives and extrema. Prerequisite: PreCalculus 12 (or equivalent) with a grade of at least B, or MATH 100 with a grade of at least C, or achieving a satisfactory grade on the Simon Fraser University Calculus Readiness Test. Students with credit for either MATH 150, 151 or 154 may not take MATH 157 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Randall Pyke Justin Chan 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 

OP01  TBD  
OP02  TBD 
and one of
Riemann sum, Fundamental Theorem of Calculus, definite, indefinite and improper integrals, approximate integration, integration techniques, applications of integration. Firstorder separable differential equations and growth models. Sequences and series, series tests, power series, convergence and applications of power series. Prerequisite: MATH 150 or 151; or MATH 154 or 157 with a grade of at least B. Students with credit for MATH 155 or 158 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Vijaykumar Singh 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Brenda Davison 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D300 
Brenda Davison 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD  
OP03  TBD 
Designed for students specializing in the biological and medical sciences. Topics include: the integral, partial derivatives, differential equations, linear systems, and their applications; mathematical models of biological processes. Prerequisite: MATH 150, 151 or 154; or MATH 157 with a grade of at least B. Students with credit for MATH 152 or 158 may not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jonathan Jedwab Natalia Kouzniak 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
D200 
Natalia Kouzniak Jonathan Jedwab 
Mo, We, Fr 8:30 AM – 9:20 AM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Designed for students specializing in business or the social sciences. Topics include: theory of integration, integration techniques, applications of integration; functions of several variables with emphasis on double and triple integrals and their applications; introduction to differential equations with emphasis on some special firstorder equations and their applications; sequences and series. Prerequisite: MATH 150 or 151 or 154 or 157. Students with credit for MATH 152 or 155 may not take MATH 158 for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

E100 
Mo 4:30 PM – 5:20 PM We 4:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 

OP01  TBD 
and one of
Linear equations, matrices, determinants. Introduction to vector spaces and linear transformations and bases. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. An emphasis on applications involving matrix and vector calculations. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 240 make not take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Luis Goddyn 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
D200 
Seyyed Aliasghar Hosseini 
Mo, We, Fr 1:30 PM – 2:20 PM 
REMOTE LEARNING, Burnaby 
OP01  TBD  
OP02  TBD 
Linear equations, matrices, determinants. Real and abstract vector spaces, subspaces and linear transformations; basis and change of basis. Complex numbers. Eigenvalues and eigenvectors; diagonalization. Inner products and orthogonality; least squares problems. Applications. Subject is presented with an abstract emphasis and includes proofs of the basic theorems. Prerequisite: MATH 150 or 151; or MACM 101; or MATH 154 or 157, both with a grade of at least B. Students with credit for MATH 232 cannot take this course for further credit. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Jonathan Jedwab 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
OP01  TBD 
** strongly recommended
+ The following substitutions are also permitted. They may not also be used to satisfy the upper division requirements. MACM 409  Numerical Linear Algebra: Algorithms, Implementation and Applications (3) for MACM 203. MACM 401  Introduction to Computer Algebra (3) for MACM 204. MACM 442  Cryptography (3) for MACM 204.
++ with a B grade or better
Upper Division Requirements
Students complete 54 units, including all of
Analysis and design of data structures for lists, sets, trees, dictionaries, and priority queues. A selection of topics chosen from sorting, memory management, graphs and graph algorithms. Prerequisite: CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.
Section  Instructor  Day/Time  Location 

D100 
Qianping Gu 
Mo, We, Fr 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 
This course introduces students to formal models of computations such as Turing machines and RAMs. Notions of tractability and intractability are discusses both with respect to computability and resource requirements. The relationship of these concepts to logic is also covered. Prerequisite: MACM 201.
Models of computation, methods of algorithm design; complexity of algorithms; algorithms on graphs, NPcompleteness, approximation algorithms, selected topics. Prerequisite: CMPT 307.
A presentation of the problems commonly arising in numerical analysis and scientific computing and the basic methods for their solutions. Prerequisite: MATH 152 or 155 or 158, and MATH 232 or 240, and computing experience. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Steven Ruuth 
Mo, We, Fr 12:30 PM – 1:20 PM 
REMOTE LEARNING, Burnaby 
D101 
We 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
We 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
We 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Th 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 

D105 
Th 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 

D106 
Th 11:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby 

D107 
Th 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 
Linear programming modelling. The simplex method and its variants. Duality theory. Postoptimality analysis. Applications and software. Additional topics may include: game theory, network simplex algorithm, and convex sets. Prerequisite: MATH 150, 151, 154, or 157 and MATH 240 or 232. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Mahsa Faizrahnemoon 
Mo, We, Fr 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 
D101 
Tu 2:30 PM – 3:20 PM 
REMOTE LEARNING, Burnaby 

D102 
Tu 3:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby 

D103 
Tu 4:30 PM – 5:20 PM 
REMOTE LEARNING, Burnaby 

D104 
Tu 9:30 AM – 10:20 AM 
REMOTE LEARNING, Burnaby 
The integers, fundamental theorem of arithmetic. Equivalence relations, modular arithmetic. Univariate polynomials, unique factorization. Rings and fields. Units, zero divisors, integral domains. Ideals, ring homomorphisms. Quotient rings, the ring isomorphism theorem. Chinese remainder theorem. Euclidean, principal ideal, and unique factorization domains. Field extensions, minimal polynomials. Classification of finite fields. Prerequisite: MATH 240 (or MATH 232 with a grade of at least B). Students with credit for MATH 332 may not take this course for further credit. Quantitative.
Fundamental concepts, trees and distances, matchings and factors, connectivity and paths, network flows, integral flows. Prerequisite: MACM 201 (with a grade of at least B). Quantitative.
and one of
This course aims to give the student an understanding of what a modern operating system is, and the services it provides. It also discusses some basic issues in operating systems and provides solutions. Topics include multiprogramming, process management, memory management, and file systems. Prerequisite: CMPT 225 and (CMPT 295 or (ENSC 251 and ENSC 252)).
Section  Instructor  Day/Time  Location 

D100 
Tianzheng Wang 
Mo 10:30 AM – 11:20 AM Th 10:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
D200 
Mo 10:30 AM – 11:20 AM Th 10:30 AM – 12:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
Data communication fundamentals (data types, rates, and transmission media). Network architectures for local and wide areas. Communications protocols suitable for various architectures. ISO protocols and internetworking. Performance analysis under various loadings and channel error rates. Prerequisite: CMPT 225 and (MATH 151 or MATH 150). MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 151 (MATH 150).
Section  Instructor  Day/Time  Location 

D100 
Ouldooz Baghban Karimi 
Mo 2:30 PM – 3:20 PM Th 2:30 PM – 4:20 PM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
and one of
This course provides an introduction to the fundamentals of computer graphics. Topics include graphics display and interaction hardware, basic algorithms for 2D primitives, antialiasing, 2D and 3D geometrical transformations, 3D projections/viewing, Polygonal and hierarchical models, hiddensurface removal, basic rendering techniques (color, shading, raytracing, radiosity), and interaction techniques. Prerequisite: CMPT 225 and MATH 232 or 240.
Section  Instructor  Day/Time  Location 

D100 
KangKang Yin Yagiz Aksoy Richard Zhang 
Tu 10:30 AM – 12:20 PM Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby REMOTE LEARNING, Burnaby 
This course covers the key components of a compiler for a high level programming language. Topics include lexical analysis, parsing, type checking, code generation and optimization. Students will work in teams to design and implement an actual compiler making use of tools such as lex and yacc. Prerequisite: MACM 201, (CMPT 295 or ENSC 215) and CMPT 225.
and one of
Theoretical and computational methods for investigating the minimum of a function of several real variables with and without inequality constraints. Applications to operations research, model fitting, and economic theory. Prerequisite: MATH 232 or 240, and 251. Quantitative.
Section  Instructor  Day/Time  Location 

D100 
Randall Pyke Randall Pyke 
Mo, We, Fr 10:30 AM – 11:20 AM 
REMOTE LEARNING, Burnaby 
D102 
Th 5:30 PM – 6:20 PM 
REMOTE LEARNING, Burnaby 
Review of the basics of probability, including sample space, random variables, expectation and conditioning. Applications of Markov chains, the exponential distribution and the Poisson process from science and industry. Applications may include inventory theory, queuing, forecasting, scheduling and simulation. Prerequisite: STAT 270 and (MATH 232 or MATH 240). Quantitative.
Formulation, analysis and simulation of continuous mathematical models. Applications may be selected from topics in physics, biology, engineering and economics. Prerequisite: MATH 251 and MATH 260. Students with credit for MATH 461 or MATH 761 may not complete this course for further credit. Quantitative.
and additional course work to total 27 upper division MATH units and 27 upper division CMPT units including core requirements. MACM courses are counted in an alternating fashion towards the MATH and CMPT requirements, starting with the first MACM course completed counting towards either MATH or CMPT. 18 units must be completed at the 400 division or higher, including at least six units each of CMPT and MATH.
Students are encouraged to take either
Students must submit a proposal to the Undergraduate Chair, including the name and signature of the supervising faculty member(s). Students must complete a project report and make a project presentation. This course can satisfy the research project requirements for Computing Science honours students. Prerequisite: Students must have completed 90 units, including 15 units of upper division CMPT courses, and have a GPA of at least 3.00. The proposal must be submitted to the Undergraduate Chair at least 15 days in advance of the term. The proposal must be signed by the supervisor(s) and the undergraduate chair.
or both of
Students will develop skills required for mathematical research. This course will focus on communication in both written and oral form. Students will write documents and prepare presentations in a variety of formats for academic and nonacademic purposes. The LaTeX document preparation system will be used. Course will be given on a pass/fail basis. Corequisite: MATH 499W.
An honours research project in mathematics is an original presentation of an area or problem in mathematics. A typical project is an original synthesis of knowledge generated from students research experience. A project can contain substantive, original mathematics, but need not. The presentation consists of a written report and an oral presentation both of which must be completed before the end of the exam period. Prerequisite: 18 credits of upper division MATH or MACM courses. Must be in an honours program with a GPA of at least 3.0. Corequisite: MATH 498. Writing.
Other Requirements
Of the total 120 units required for honours, at least 60 must be from the upper division.
The program is subject to Faculty of Science and University regulations. Course and prerequisite admission is subject to departmental requirements. MACM major graduation is contingent upon a cumulative grade point average (CGPA) and upper division grade point average (UDGPA) of 3.00 or better. Students must also achieve a 3.00 or better CGPA and UDGPA in each of the CMPT, MACM and MATH designations.
Admission, continuation and graduation in the MACM honours is contingent upon 3.00 or better on all relevant GPAs. Faculty of Applied Sciences residency requirements appy to the computing science courses used toward the program.
Cooperative Education and Work Experience
All computing science students are strongly encouraged to explore the opportunities that Work Integrated Learning (WIL) can offer. Please contact a computing science or mathematics coop advisor during the first year of studies to ensure that you have all of the necessary courses and information to help plan for a successful coop experience.
Visit http://www.cs.sfu.ca/undergraduate/coop.html for more computing science information, or for mathematics, http://www.sfu.ca/coop/contact#science.
University Honours Degree Requirements
Students must also satisfy University degree requirements for degree completion.
Writing, Quantitative, and Breadth Requirements
Students admitted to Simon Fraser University beginning in the fall 2006 term must meet writing, quantitative and breadth requirements as part of any degree program they may undertake. See Writing, Quantitative, and Breadth Requirements for universitywide information.
WQB Graduation Requirements
A grade of C or better is required to earn W, Q or B credit
Requirement 
Units 
Notes  
W  Writing 
6 
Must include at least one upper division course, taken at Simon Fraser University within the student’s major subject  
Q  Quantitative 
6 
Q courses may be lower or upper division  
B  Breadth 
18 
Designated Breadth  Must be outside the student’s major subject, and may be lower or upper division 6 units Social Sciences: BSoc 6 units Humanities: BHum 6 units Sciences: BSci 
6 
Additional Breadth  6 units outside the student’s major subject (may or may not be Bdesignated courses, and will likely help fulfil individual degree program requirements) Students choosing to complete a joint major, joint honours, double major, two extended minors, an extended minor and a minor, or two minors may satisfy the breadth requirements (designated or not designated) with courses completed in either one or both program areas. 
Residency Requirements and Transfer Credit
 At least half of the program's total units must be earned through Simon Fraser University study.
 At least two thirds of the program's total upper division units must be earned through Simon Fraser University study.
Please see Faculty of Applied Sciences Residency Requirements for further information.
Elective Courses
In addition to the courses listed above, students should consult a Mathematics or Computing Science advisor to plan the remaining required elective courses.