Two Sum — LeetCode #1 (Easy)
The article explains the 'Two Sum' problem on LeetCode, where the goal is to find the indices of two numbers in an array that add up to a given target. A naive solution using nested loops has O(n²) time complexity, while an optimal solution uses a hash map for O(n) time. The key insight is to check for the complement (target minus current value) before storing the current value in the map.
- ▪The Two Sum problem requires returning the indices of two numbers that sum to a target value.
- ▪The optimal solution uses a single-pass hash map to store values and their indices, achieving O(n) time complexity.
- ▪A common pitfall in interviews is incorrectly ordering the check and insert operations, which can lead to using the same element twice.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 245317) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Shubham Gupta for Logixy Posted on May 17 • Originally published at youtu.be Two Sum — LeetCode #1 (Easy) #leetcode #python #algorithms #array TL;DR Single-pass hash map lookup: store each number's index as you go, check for the complement before storing. O(n) time, O(n) space. The Problem Given an array of integers nums and an integer target, return the indices of the two numbers that add up to target.
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