Strategy for coding solutions

These are strategies for tackling data structures and algorithms in coding questions.

If the given input is a sorted (array, list, or matrix), then we will be using a variation of Binary Search or a Two Pointers strategy

If we are dealing with top/maximum/minimum/closest 'k' elements among 'n' elements, we will be using a Heap

If we need to try all combination (or permutations) of the input, we can either use recursive Backtracking or iterative Breadth-First Search.

Most of the questions related toTrees or Graphs can be solved either through Breadth-First Search or Depth-First Search.

Every recursive solution can be converted to an iterative solution using a stack.

If for a problem, there exists a brute-force solution in O(n2) time and O(1) space, there must exist two other solutions: 1) Using a Map or a Set for O(n) time and O(n) space, 2) Using sorting for O(n log n) time and O(1) space.

If the problem is asking for optimization (e.g., maximization or minimization), we will need to use Dynamic Programming to solve it.

If we need to find some common substring among a set of strings, we will be using a HashMap or a Trie.

If we need to search among a bunch of strings, Trie will be the best data structure.

If the problem involves a LinkedList and we can't use extra space, then use Fast & Slow Pointer approach.

Happy Coding 🎉