Spring 2023 - CMPT 479 D100

Special Topics in Computing Systems (3)

Software Engineering

Class Number: 6722

Delivery Method: In Person


  • Course Times + Location:

    Jan 4 – Apr 11, 2023: Tue, 12:30–2:20 p.m.

    Jan 4 – Apr 11, 2023: Fri, 12:30–1:20 p.m.

  • Exam Times + Location:

    Apr 24, 2023
    Mon, 3:30–6:30 p.m.

  • Prerequisites:

    CMPT 300 with a minimum grade of C-.



Current topics in computing systems depending on faculty and student interest.


How can we create software that is maintainable, reliable, and secure? How can we treat software systems as subjects for analysis? How can we automate challenging tasks like finding vulnerabilities or even programming itself? This course examines both classic and cutting edge answers to these software engineering questions. This course will explore modern aspects of software engineering including design, reliability, performance, and security. Beyond manual design and programming issues, students will gain experience with techniques for automating aspects of software engineering and treating programs themselves as data that can be analyzed, transformed, or automatically generated. The material will be hands-on, with several small projects in a variety of programming languages throughout the semester. Students are expected to learn core techniques used in program analysis and to ultimately apply them. Students will also be expected to complete a term project in a direction of their choice based on material from the course. The term project will involve building a tool that automates some useful analysis/task within software engineering. Introductory projects will involve programming in Python, Java, and C++. Term projects can be done using a language of student preference. Students should have completed CMPT 300 before enrolling. CMPT 379 is recommended but not required.


  • Classic design and architecture
  • Performance analysis
  • Static and dynamic program analysis
  • Software security (offense and defense)
  • Automated debugging & defect investigation
  • Automated program synthesis
  • Automated test generation
  • Concurrency and parallelism




Assignments: 50% Exams: 25% Term Project: 25% Grading criteria are subject to change.



Reference Books

  • Working Effectively with Legacy Code, Feathers, Michael, Prentice Hall, 9780131177055
  • Principles of Program Analysis, Nielson, Flemming, Nielson, Hanne R., Hankin, Chris, Springer, 9783642084744
  • Engineering a Compiler, Cooper, Keith, Torczon, Linda, Elsevier Science & Technology Books, 9780120884780
  • Security Engineering: A Guide to Building Dependable Distributed Systems, Anderson, Ross J., Wiley & Sons, Incorporated, 9780470068526
  • Writing Solid Code 2nd Edition, Maquire, Steve, Greyden Press, 9781570740558


Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:


SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html