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19 articles
Two Sum is the most asked interview problem at Google, Amazon and Meta. Learn every approach from O(n²) brute force to O(n) HashMap with C, C++, Java, JavaScript and Python solutions.
Find the intersection of two integer arrays including duplicates. Each element appears as many times as it shows in both arrays.
Group strings that are anagrams of each other. Use sorted string as HashMap key. O(n*k*log k) time. Full solutions in 5 languages.
Find length of longest substring without repeating characters. Optimal O(n) sliding window with HashMap tracking last seen positions.
Count subarrays summing to k. Classic prefix sum + HashMap trick: if prefix[j]-prefix[i]=k then prefix[i]=prefix[j]-k. O(n) time.
Find k most frequent elements. Approach 1: min-heap O(n log k). Approach 2: bucket sort O(n). Full 5-language solutions.
Group anagrams, find anagram indices, and count anagram occurrences. Three approaches: sort key O(nk log k), frequency tuple O(nk), and sliding window O(n+k).
Find the smallest substring of s containing all characters of t using an expanding/contracting two-pointer window with frequency counting. O(n) time.
Find the longest substring with at most k distinct characters using a sliding window with a character frequency map. O(n) time.
Count subarrays with sum equal to k using prefix sums and a hashmap. O(n) time by tracking how many times each prefix sum has occurred.
Comprehensive coverage of Two Sum, Two Sum II (sorted), 3Sum, and 4Sum. Amazon frequently tests these variants to gauge understanding of hashmap vs two-pointer trade-offs.
Create a deep copy of an undirected graph using DFS with a HashMap to track visited/cloned nodes. Meta tests this to evaluate graph traversal and pointer manipulation.
Implement an LRU (Least Recently Used) cache with O(1) get and put using a doubly linked list and hashmap. Full 5-language solutions.
Implement an LFU cache with O(1) get and put. Uses two hashmaps and per-frequency doubly linked lists to track access frequency and recency simultaneously.
Implement a file system that creates paths and associates values with them. Uses a Trie or HashMap to map full paths to values with O(L) operations.
Design a key-value store that returns values at or before a given timestamp. Uses a hashmap of sorted (timestamp, value) lists with binary search for O(log n) get.
Design a log storage system that retrieves log IDs within a timestamp range at a specified granularity (Year, Month, Day, Hour, Minute, Second).
Design an in-memory key-value database that supports set, get, delete, and rank operations. Demonstrates combining hashmaps with sorted structures for efficient multi-key queries.
Design a URL shortener like TinyURL that encodes long URLs to short codes and decodes them back. Uses base-62 encoding with a counter or random string generation.