7 Must-Know Big-O Time Complexities for Coding Interviews
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7 Must-Know Big-O Time Complexities for Coding Interviews Understanding Big-O is essential for solving DSA problems and writing efficient code. Here are 7 time complexities every developer should know: O(1) – Constant: Array index access. O(log n) – Logarithmic: Binary Search. O(n) – Linear: Traversing an array. O(n log n) – Linearithmic: Merge Sort. O(n²) – Quadratic: Nested loops, Bubble Sort. O(2ⁿ) – Exponential: Generating subsets. O(n!) – Factorial: Generating permutations. How to remember them: O(1): Input size doesn't affect runtime. O(log n): Problem size reduces at each step. O(
Posted by SCR (8.5k followers) 3 h ago · 9 likes · 312 views · view the original post on X. Kept by the Dev Radar as Careers & learning.
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