Spring 2022 - CMPT 307 D200
Data Structures and Algorithms (3)
Class Number: 6073
Delivery Method: In Person
Course Times + Location:
We 3:30 PM – 4:20 PM
SSCK 9500, Burnaby
Fr 2:30 PM – 4:20 PM
SSCC 9001, Burnaby
1 778 782-4685
Prerequisites:CMPT 225, MACM 201, (MATH 150 or MATH 151), and (MATH 232 or MATH 240), all with a minimum grade of C-. MATH 154 or MATH 157 with a grade of at least B+ may be substituted for MATH 150 or MATH 151.
Design and analysis of efficient data structures and algorithms. General techniques for building and analyzing algorithms (greedy, divide & conquer, dynamic programming, network flows). Introduction to NP-completeness.
The objective of this course is to introduce concepts and problem-solving techniques that are used in the design and analysis of efficient algorithms. This is done by studying various algorithms, algorithmic techniques, data structures and applications.
- Introduction and Mathematical Preliminaries (Review): Models of Computation, Big-O Analysis
- Searching and Sorting: Divide & Conquer Paradigm, Analysis of Recurrences, Master Method
- Sorting and Order Statistics: Heapsort, Quicksort, Non-comparison sorts, Lower bounds, Median
- Randomized algorithms, Average case analysis
- Simple Data Structures: Lists, Stacks, Queues, Trees
- Dictionaries and Priority Queues: [Balanced] Binary search trees, Heaps
- Graphs: Representations, Path Searching, Spanning Trees
- Amortized Analysis: Aggregate, Accounting, Potential Methods
- Optimization Problems: Dynamic programming, Greedy algorithms
The course has a final examination, homework assignments, and at least one midterm examination/test/quiz. 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).
MATERIALS + SUPPLIES:
Algorithm Design , J. Kleinberg, E. Tardos, Addison Wesley, 2006, 9780321295354
Algorithms, S. Dasgupta, C. Papadimitriou, U. Vazirani, McGraw-Hill Higher Education, 2008, 9780073523408, An e-text version is available: ISBN 9780077244330
Introduction to Algorithms (3rd Edition), T.H. Cormen, C.E. Leiserson, R.L. Rivest, C. Stein, MIT Press, 2009
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TEACHING AT SFU IN SPRING 2022
Teaching at SFU in spring 2022 will involve primarily in-person instruction, with safety plans in place. Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
Enrolling in a course acknowledges that you are able to attend in whatever format is required. You should not enroll in a course that is in-person if you are not able to return to campus, and should be aware 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.
Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (email@example.com or 778-782-3112) as early as possible in order to prepare for the spring 2022 term.