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Store the results of subproblems to avoid redundant computations, often using a table.

Find occurrences of a substring within a string using algorithms like Knuth-Morris-Pratt or Rabin-Karp.

Find an element within a data structure, commonly using linear search or binary search.

Build up a solution piece by piece by choosing the best option at each step, without revisiting previous decisions.

Explore all potential solutions in a systematic way and backtrack as soon as it becomes clear that a path does not lead to a solution.

Model a system as a network seeking to find the maximum flow from the source to sink, often using Ford-Fulkerson algorithm or Edmonds-Karp algorithm.

Solve a problem by expressing its solution in terms of smaller instances of the same problem.

Break the problem down into smaller subproblems of the same type and solve these subproblems recursively.

Explore a graph either using depth-first search (DFS) or breadth-first search (BFS) to visit nodes.