Spring 2021 - CMPT 307 D100
Data Structures and Algorithms (3)
Class Number: 6656
Delivery Method: In Person
Course Times + Location:
Mo, We, Fr 11:30 AM – 12:20 PM
REMOTE LEARNING, Burnaby
Exam Times + Location:
Apr 25, 2021
3:30 PM – 6:30 PM
REMOTE LEARNING, Burnaby
1 778 782-6705
Prerequisites:CMPT 225, MACM 201, MATH 151 (or MATH 150), and MATH 232 or 240.
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.
The objective of this course is to introduce concepts and problem-solving techniques for the design and analysis of efficient algorithms through studying data structures, algorithms, and algorithmic techniques.
COURSE-LEVEL EDUCATIONAL GOALS:
- Introduction 1: algorithm design and analysis examples, computation models, Big-O analysis
- Introduction 2: divide and conquer, analysis of recurrence, randomized algorithms
- Sorting and order statistics: Heapsort, Quicksort, other sorting problems
- Simple data structures: lists, stacks, queues, trees, hash tables
- Algorithm design and analysis techniques, dynamic programming, greedy, amortized analysis
- Advanced data structures, B-trees, Fibonacci heaps
- Graph algorithms, graph search, minimum spanning trees, shortest paths
- Selected topics, NP-completeness, string matching, maximum flow
The lectures is planned to be delivered online at the scheduled class time (currently 11:30-12:20, M/W/F), recorded and posted at some website. The course has a final examination, homework assignments, and quizzes or midterms. The grade distribution will be announced during the first week of classes.
Students must attain an overall passing grade on the weighted average of exams in the course in order to obtain a clear pass (C- or better).
- Introduction to Algorithms (3rd Edition), T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, MIT Press, 2009, 9780262033848
- Algorithm Design , J. Kleinberg, E. Tardos, Addison-Wesley, 2006, 9780321295354
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site 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
TEACHING AT SFU IN SPRING 2021
Teaching at SFU in spring 2021 will be conducted primarily through remote methods. There will be in-person course components in a few exceptional cases where this is fundamental to the educational goals of the course. Such course components will be clearly identified at registration, as will course components that will be “live” (synchronous) vs. at your own pace (asynchronous). Enrollment acknowledges that remote study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for in-person classes. To ensure you can access all course materials, we recommend you have access to a computer with a microphone and camera, and the internet. In some cases your instructor may use Zoom or other means requiring a camera and microphone to invigilate exams. If proctoring software will be used, this will be confirmed in the first week of class.Students with hidden or visible disabilities who believe they may need class or exam accommodations, including in the current context of remote learning, are encouraged to register with the SFU Centre for Accessible Learning (email@example.com or 778-782-3112).