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Development of more sophisticated ideas in data type and structure, with an introduction to the connection between data structures and the algorithms they support. Data abstraction. Controlled access structures. Trees, lists, stacks, queues, graphs, arrays, hash tables. Algorithm design strategies such as divide and conquer. Elementary techniques for analysis; asymptotic analysis, recursion equations, estimation methods, elementary combinatorial arguments. Examination of problem areas such as searching and sorting, and the indicated representations and algorithms. The student will use the techniques learned in this course and in previous courses to solve a number of logically complex programming problems using pseudocode, with an emphasis on establishing algorithmic correctness and estimating time and space complexity.
Pre-Reqs: COMP 1020 Computing II, MATH 3220 Discrete Structures ll and MATH 3860 Probability & Statistics I.