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COMP-SCI 404
Introduction to Algorithms and Complexity
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A rigorous review of asymptotic analysis techniques and algorithms: from design strategy (such as greedy, divide-and-conquer, and dynamic programming) to problem areas (such as searching, sorting, shortest path, spanning trees, transitive closures, and other graph algorithms, string algorithms) arriving at classical algorithms with supporting data structures for efficient implementation. Throughout, the asymptotic complexity is studied in worst case, best case, and average case for time and/or space, using appropriate analysis techniques (recurrence relations, amortization). Introduction to the basic concepts of computability and NP-complete theory.
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Prerequisite(s):
COMP-SCI 291, COMP-SCI 303 or COMP-SCI 352, (Must be passed with a C or higher)
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Corequisite(s):
(Preferred) COMP-SCI 394R and MATH 300
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Faculty:
School of Computing & Engineer
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Department:
Comp Sci & Elect Engr
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