Tabulation
Tabulation is a dynamic programming technique used to solve optimization problems by building a table (usually an array or matrix) that stores solutions to subproblems in a bottom-up, iterative manner. It involves filling the table systematically, starting from the smallest subproblems and using their results to compute larger ones, ensuring each subproblem is solved only once. This approach is particularly effective for problems with overlapping subproblems and optimal substructure, such as computing Fibonacci numbers, shortest paths, or knapsack problems.
Developers should learn tabulation when working on algorithmic challenges or performance-critical applications that require efficient solutions to recursive problems, as it avoids the overhead of recursion and memoization by using iteration, which can be faster and more memory-efficient in many cases. It is especially useful in competitive programming, data structure implementations, and system design where predictable performance and avoiding stack overflow are priorities, such as in pathfinding algorithms or resource allocation tasks.