Course Catalog URL:
COM S 311
Offered during Fall and Spring Semesters each year.
- Credits and contact hours: 3 credits, 4 contact hours
- Instructor’s or course coordinator’s name: Samik Basu, Pavankumar Aduri
- Text book, title, author, and year: Algorithm Design, Kleinberg and Eva Tardos
- Other supplemental materials: None
Specific course information
- Brief description of the content of the course: Basic techniques for design and analysis of algorithms. Sorting, searching, graph algorithms, string matching, and NP-completeness. Design techniques such as dynamic programming, divide and conquer, greedy method, and approximation. Asymptotic, worst-case, average-case and amortized analyses. Topics from advanced data structures such as balanced trees and hashing.
- Prerequisites or co-requisites: Minimum of C – in COM S 228; MATH 166, ENGL 250, and COM S 230 or CPR E 310
- Required, elective, or selected elective? Required
Specific goals for the course
- Specific outcomes of instruction: Algorithms are the basic recipes for solving computational problems. Upon completion of this course, students should:
- Know a set of “standard algorithms” (and data structures) and be able to model a problem to use them.
- Gain a strong foundation in designing algorithms based on common techniques, including greedy, divide and conquer, dynamic programming, etc. (1)
- Be able to reason about correctness of algorithms, either by proof or providing a counter example. (6)
- Be able to recognize intractable problems and have an idea on how to develop approximation algorithms.
- Be able to implement algorithms given their description.
Brief list of topics to be covered
- Run time, Big O and asymptotic bounds
- Sorting and searching
- Divide and conquer
- Graphs and graph algorithms
- Greedy algorithms
- Public Key cryptography, RSA algorithm
- Dynamic programming
- Approximation algorithms & heuristics