Hash Maps mind map
Key–value lookups, counting, and frequency maps.
Core idea: Trade memory for an O(1) question: what must I know about what I have already seen?
Mnemonic: Key → ask → remember · Cost: O(n) space · O(1) average lookup
Count: Frequency & signature
Signal: Identity depends on occurrences rather than position.
Move: Map each key to a count; sort or serialize counts when equivalent groups need one key.
Examples: Ransom Note, Top K Frequent, Group Anagrams
Match: Complement lookup
Signal: A future value can complete the answer with something already seen.
Move: Ask for the complement before storing the current value and its useful metadata.
Examples: Two Sum, Pair Difference, Isomorphic Strings
Remember: Identity & latest position
Signal: Objects must be cloned, deduplicated, or tracked across time.
Move: Store original → copy, or value → most useful index, then wire or bound from the map.
Examples: Copy Random List, Longest Unique Substring, LRU Cache
Balance: Prefix lookup
Signal: A subarray is defined by a target sum or equalized counts.
Move: Look for the earlier prefix that makes the current prefix complete the target.
Examples: Subarray Sum Equals K, Contiguous Array, Divisible Subarrays