Must-Know Data                Structures for                Coding Interviews

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Array

Arrays are ordered collections with constant time access to elements. Solve questions like finding missing number, two sum, max subarray, etc.

1

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String

Strings are character collections crucial for text processing, NLP, & info retrieval. Solve tasks like reverse string, valid palindrome, longest substring, etc.

2

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LIFO data structures, useful for memory allocation and syntax parsing. Solve tasks like parentheses validation, min stack, simplifying path, and more.

Stacks

3

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FIFO structures for orderly storage. Enqueue & dequeue operations suit OS, message systems, & web servers. Solve tasks like implementing stack, design circular queue, & more.

Queues

4

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Dynamic nodes for variable data. Perfect for managing data sizes. Tasks like reversing and merging lists are common.

Linked List

5

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Hierarchical structures for relationships, searching, and sorting. Solve tasks involving tree depth, validation, and traversal.

Trees

6

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Binary tree-based structures for priority queues. Solve tasks like finding largest elements, merging sorting lists, sorting characters by frequency, and more.

Heaps

7

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Complex relationships modeled with nodes and edges. Handy for network operations, shortest paths, and cycle detection.

Graphs

8

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Key-value pairs with quick access. Widely used in databases and search engines. Solve tasks involving anagrams and groupings.

Hash Tables

9

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Two-dimensional arrays for linear algebra and data analysis. Solve problems like matrix transformations and pathfinding.

Matrix

10

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