0 or 3 credits
Fall 2025 Practice Study Observation Lecture Distance Learning Upper Division
Techniques for analyzing the time and space requirements of algorithms. Application of these techniques to sorting, searching, pattern-matching, graph problems, and other selected problems. Brief introduction to the intractable (NP-hard) problems.
Learning Outcomes1Use big O-notation to give asymptotic time and space bounds of algorithms.
2Explain the use of big-Omega, big-Theta, and little-o notations.
3Use recurrence relations to determine the time complexity of recursive algorithms.
4Solve recurrence relations commonly arising in algorithm design.
5Give examples that illustrate time-space trade-offs of algorithms.
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