Dynamic Programming: Memoization and Tabulation
Students will learn basic search techniques to find specific information within a list or collection of data.
Key Questions
- Identify the two structural properties—overlapping subproblems and optimal substructure—that make a problem amenable to dynamic programming, and construct a counterexample where only one property holds.
- Design a bottom-up tabulation solution for the 0/1 knapsack problem, derive its time and space complexity, and explain how space can be reduced from O(nW) to O(W).
- Compare a naive recursive solution, a top-down memoized solution, and a bottom-up tabulation solution for the longest common subsequence problem in terms of correctness, time complexity, and practical performance.
MOE Syllabus Outcomes
Suggested Methodologies
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