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Recursive Optimization with Memoization

#algorithms #optimization #dynamic-programming

Optimize a highly inefficient recursive algorithm and analyze the time-space trade-off.

Given the following naive recursive function for calculating the nth term of a custom tribonacci sequence with distinct modulo operations: [Function Pseudocode]. Analyze its time complexity and identify the redundant calculations. Refactor the code to implement memoization (top-down dynamic programming). Then, convert the solution into an iterative approach (bottom-up) with O(1) space complexity. Provide a mathematical proof of correctness for the iterative version and compare the stack memory usage between the three versions.