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CS 31100  Competitive Programming II  
Credit Hours: 2.00. CP2 teaches experienced programmers additional techniques to solve interview and competitive programming problems and builds on material learned in CP1. This includes specific algorithmic techniques such as [shortest paths, topological sort, MST, union find, range queries], advanced algorithms surrounding trees and DAGs, advanced problem types in [dynamic programming, backtracking/simulation, mathematics, string processing], and more. It can be viewed as a programming complement to CS 38100, with some overlap in content.
2.000 Credit hours Syllabus Available Levels: Graduate, Professional, Undergraduate Schedule Types: Distance Learning, Lecture Offered By: College of Science Department: Computer Science Course Attributes: Provost Low Enroll Perm Waiver, Upper Division May be offered at any of the following campuses: West Lafayette Learning Outcomes: 1. Differentiate between advanced categories of problems in computer science including backtracking/simulation, advanced dynamic programming, advanced graphs (including trees and DAGs), mathematics, string processing, and range queries, as well as subcategories in each of these categories. 2. Implement wellknown solutions (as discussed in class) to advanced categories of problems in computer science (listed in LO1). 3. Identify when a problem spans multiple categories of problems (as listed in LO1) 4. Design algorithms to solve problems that span multiple categories of problems. 5. Use new/novel algorithms to solve advanced problems. 6. Recognize key characteristics of certain problem types listed in LO1. 7. Classify an advanced problem by those key characteristics. 8. Deconstruct an advanced problem into subproblems that can be solved individually. 9. Determine runtime and space usage of a potential solution using bigO notation to judge if the potential solution will work. 10. Create an efficient solution to a problem based on analysis of the problem type, the deconstructed problem parts, and the time and space constraints of the problem. 11. Reflect on how one came up with a solution to a problem in order to better recognize patterns in problem types. Restrictions: Must be enrolled in one of the following Majors: Computer Science Computer Science Honors Data Science Data Science First Year Prerequisites: Undergraduate level CS 21100 Minimum Grade of C and Undergraduate level CS 25100 Minimum Grade of C Short Title: Competitive Programming II Course Configurations:
