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CSCI-C 455 Analysis of Algorithms

3-4 credits

  • Prerequisites: CSCI-C 310, CSCI-C 343, or CSCI 36200
  • Delivery: On-Campus
  • Learning Outcomes

    1. Analyze the correctness of algorithms using inductive proofs and loop invariants.
    2. Analyze the worst-case running times of algorithms using asymptotic analysis.
    3. Analyze the average-case running times of algorithms with probabilistic running times.
    4. Explain the basic properties of randomized algorithms and methods for analyzing them.
    5. Identify when an algorithm design situation requires a divide and conquer, dynamic programming, or greedy strategy and implement it.
    6. Implement the major algorithms for sorting.
    7. Explain the data structures used to implement dynamic sets and analyze the operations performed on them.


    There is not a syllabus available for this course.