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Coding Interview

Learn Coding Interview as a connected topic across chapters, concepts, simulations, and interview reasoning.

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Learn Coding Interview as a connected topic across chapters, concepts, simulations, and interview reasoning.

How this topic helps

Algorithms
Data Structures
Java
Heaps

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16 matched articles

Article 1Big O Notation Explained: Time Complexity, Space Complexity, and Why They Matter in InterviewsTLDR: Big O notation describes how an algorithm's resource usage grows as input size grows — not how fast it runs on your laptop. Learn to identify the 7 complexity classes (O(1) through O(n!)), deriv34 minArticle 2Two Pointer Technique: Solving Pair and Partition Problems in O(n)TLDR: Place one pointer at the start and one at the end of a sorted array. Move them toward each other based on a comparison condition. Every classic pair/partition problem that naively runs in O(n²) 16 minArticle 3Tries (Prefix Trees): The Data Structure Behind AutocompleteTLDR: A Trie stores strings character by character in a tree, so every string sharing a common prefix shares those nodes. Insert and search are O(L) where L is the word length. Tries beat HashMaps on 17 minArticle 4Sliding Window Technique: From O(n·k) Scans to O(n) in One PassTLDR: Instead of recomputing a subarray aggregate from scratch on every shift, maintain it incrementally — add the incoming element, remove the outgoing element. For a fixed window this costs O(1) per16 minArticle 5Merge Intervals Pattern: Solve Scheduling Problems with Sort and SweepTLDR: Sort intervals by start time, then sweep left-to-right and merge any interval whose start ≤ the current running end. O(n log n) time, O(n) space. One pattern — three interview problems solved. 13 minArticle 6In-Place Reversal of a Linked List: The 3-Pointer Dance Every Interviewer ExpectsTLDR: Reversing a linked list in O(1) space requires three pointers — prev, curr, and next. Each step: save next, flip curr.next to point backward, advance both prev and curr. Learn this once and you 16 min

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