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๐ญ๐ฌ ๐๐ผ๐น๐ฑ๐ฒ๐ป ๐ฅ๐๐น๐ฒ๐ ๐ณ๐ผ๐ฟ ๐ฆ๐ผ๐น๐๐ถ๐ป๐ด ๐ฎ ๐๐ผ๐ฑ๐ถ๐ป๐ด ๐ค๐๐ฒ๐๐๐ถ๐ผ๐ป ๐ถ๐ป ๐ฎ๐ป Interview โค๏ธ
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A Thread ๐งต
โฆ๏ธ If we are dealing with top/maximum/minimum/closest โK' elements among 'N' elements, we will be using a Heap.
โฆ๏ธ If the given input is a sorted array or a list, we will either be using Binray Search or the Two Pointers.
โฆ๏ธ If we need to try all combinations (or permutations) of the input, we can either use Backtracking or Breadth First Search.
โฆ๏ธ Most of the questions related to Trees or Graphs can be solved either through Breadth First Search or Depth First Search.
โฆ๏ธ Every recursive solution can be converted to an iterative solution using a Stack.
โฆ๏ธ For a problem involving arrays, if there exists a solution in O(n^2)time and O(1) space, there must exist two other solutions: 1) Using a HashMap or a Set for O(n) time and O(n) space, 2) Using sorting for O(n log n) time and O(1) space.
โฆ๏ธ If a problem is asking for optimization (e.g., maximization or minimization), we will be using Dynamic Programming.
โฆ๏ธ If we need to find some common substring among a set of strings, we will be using a HashMap or a Trie.
โฆ๏ธ If we need to search/manipulate a bunch of strings, Trie will be the best data structure.
โฆ๏ธ If the problem is related to a LinkedList and we can't use extra space, then use the Fast & Slow Pointer approach.
Source: linkedin.com/posts/activityโฆ
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