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Array Data Structure Guide

Last Updated : 13 Apr, 2025
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In this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions.

  • An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous locations.
  • It offers mainly the following advantages over other data structures.
    Random Access : i-th item can be accessed in O(1) Time as we have the base address and every item or reference is of same size.
    Cache Friendliness : Since items / references are stored at contiguous locations, we get the advantage of locality of reference.
  • It is not useful in places where we have operations like insert in the middle, delete from middle and search in a unsorted data.
  • It is a fundamental and linear data structure using which we build other data structures like Stack Queue, Deque, Graph, Hash Table, etc.

Learn Basics of Array:

  • Introduction to Arrays
  • Applications of Array

Array in Different Language:

  • Arrays in C
  • Vector in C++ STL
  • Arrays in Java
  • ArrayList in Java
  • List in Python
  • Arrays in C#
  • Arrays in JavaScript

Basic Problems on Array:

  • Print Alternates
  • Linear Search
  • Largest Element
  • Second Largest
  • Largest Three
  • Leaders in an array
  • Check if Sorted
  • Remove Duplicates from Sorted
  • Generate all Subarrays
  • Reverse an Array
  • Rotate an Array
  • Zeroes to End
  • Min Increments to Make Equal
  • Min Cost to Make Size 1

Prerequisite for the Remaining Problems

  1. Binary Search
  2. Selection Sort, Insertion Sort, Binary Search, QuickSort, MergeSort, CycleSort, and HeapSort
  3. Sort in C++ / Sort in Java / Sort in Python / Sort in JavaScript
  4. Two Pointers Technique
  5. Prefix Sum Technique
  6. Basics of Hashing
  7. Window Sliding Technique

Easy Problems on Array:

  • Distinct Elements
  • Duplicate within K Distance
  • Make Even Positioned Greater
  • Sum of all Subarrays
  • Stock Buy and Sell – Multiple Transactions
  • Single Among Doubles
  • Missing Number
  • Missing and Repeating
  • Only Repeating from 1 to n-1
  • Sorted Subsequence of Size 3
  • Binary Sort
  • Stable Binary Sort
  • Stable Binary Sort with O(1) Space
  • Sort in Wave Form
  • Max Subarray Sum
  • K Concatenation Max Subarray Sum
  • Max Subarray Product
  • Equilibrium index
  • Two Sum - Find if there is a Pair
  • Two Sum - Closest Pair [More problems on 2 Sum in Medium Section]
  • Chocolate Distribution Problem
  • Union of two arrays
  • Intersection of two arrays
  • Union of two sorted arrays
  • Intersection of two sorted arrays

Medium Problems on Array:

  • Make arr[i] = i
  • Sort an array of 1 to n
  • Reorder according to given indexes
  • Minimum Swaps to Sort
  • Min in a Sorted Rotated
  • Max in a Sorted Rotated
  • Rotation Count in Rotated Sorted
  • Search in a Sorted Rotated
  • Nearly Sorted (or K sorted)
  • Product Except Self
  • K-th Largest Sum Subarray
  • Smallest missing number
  • Smallest subarray with sum greater than x
  • Inversion count
  • Merge Overlapping Intervals
  • Sort an array of 0s, 1s and 2s
  • Merge with O(1) extra space
  • Majority Element
  • Peak element
  • Count possible triangles
  • Sub-array with given sum
  • Longest Subarray with Equal 0s and 1s
  • Longest Common Span in Two Binary Arrays
  • Construct an array from its pair-sum array
  • 2 Sum - All Pairs
  • 2 Sum - Distinct Pairs
  • 3 Sum - Find Any
  • 3 Sum - Closest Triplet
  • 4 Sum - Find Any [More problems on 4 Sum in Hard Section]

Hard Problems on Array:

  • Surpasser Count
  • Trapping Rain Water
  • Top K Frequent Elements
  • Kth Missing Positive Number in a Sorted Array
  • Stock Buy and Sell - At Most K Transactions
  • Stock Buy and Sell - At Most 2 Transactions
  • Median in a Stream
  • Smallest Difference Triplet from 3 arrays
  • Max occurred in n ranges
  • 3 Sum - Distinct Triplets
  • 3 Sum - All Triplets
  • 4 Sum - Distinct Quadruples
  • 4 Sum - All Quadruples
  • 4 Sum - Closest Quadruple

Expert Problems for Competitive Programmers

  • MO’s Algorithm
  • Square Root (Sqrt) Decomposition Algorithm
  • Sparse Table
  • Range sum query using Sparse Table
  • Range Minimum Query (Square Root Decomposition and Sparse Table)
  • Range LCM Queries
  • Merge Sort Tree for Range Order Statistics
  • Minimum number of jumps to reach end
  • Space optimization using bit manipulations
  • Max value of Sum( i*arr[i]) with only rotations allowed

Quick Links :

  • ‘Practice Problems’ on Arrays
  • Top Array Interview Questions
  • ‘Quizzes’ on Arrays

Next Article
String in Data Structure

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harendrakumar123
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Article Tags :
  • DSA
  • Arrays
Practice Tags :
  • Arrays

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