Algorithms Analysis Practice Test 2025 - Free Algorithms Practice Questions and Study Guide

The statement is false because recursive routines can indeed be used in Dynamic Programming algorithms. In fact, many Dynamic Programming approaches are implemented using recursion, often combined with memoization to optimize the performance.

Dynamic Programming is a method for solving complex problems by breaking them down into simpler subproblems. Typically, it involves solving each subproblem just once and storing the results, which can be done using either an iterative or a recursive approach. When using recursion in Dynamic Programming, the approach is usually accompanied by memoization, where previously computed values are stored in a table or dictionary to avoid redundant computations.

This technique is particularly effective in problems exhibiting overlapping subproblems and optimal substructure properties, such as the Fibonacci sequence or the knapsack problem. Therefore, the flexibility of including recursion in Dynamic Programming demonstrates its capability to solve problems efficiently while leveraging the power of recursive formulations.