Day 38: Dynamic Programming - Introduction and Principles

After reading this chapter and engaging in the embedded activities and reflections, you should be able to:

• Identify inefficiency in naive recursive algorithms through repeated subproblem computation
• Implement Fibonacci calculation using naive recursion, memoization, and tabulation
• Compare time complexity of recursive vs memoized vs iterative dynamic programming approaches
• Recognize problems exhibiting overlapping subproblems property
• Recognize problems exhibiting optimal substructure property
• Distinguish between top-down (memoization) and bottom-up (tabulation) dynamic programming
• Explain when dynamic programming is an appropriate algorithmic strategy
• Trace execution of memoized recursive functions using call trees