Data Structures

Part of the Interview Prep Roadmap. Coverage ratings are explained there.

Work through alongside this section

• NeetCode 150 — the single best-known curated list for coding interviews; its array, string, linked list, stack, tree, heap, and graph sections map onto the topics below. Worth finishing as a whole rather than cherry-picking.
• Blind 75 — the shorter list NeetCode 150 grew out of, if time is tight.

Arrays & Strings

Indexing, traversal, and in-place manipulation, building up to two-pointer and sliding-window techniques.

Coverage: rich

Resources · NeetCode — Arrays & Hashing · NeetCode — Two Pointers / Sliding Window

Array Fundamentals

• Indexing and memory layout
• Fixed-size vs. dynamic arrays
• Complexity of access, insertion, and deletion

Practice

• Arrays vs. linked lists on memory, access, insert, delete — Shanghai BD
• Second maximum of an array — Bevy Commerce

Traversal & In-Place Manipulation

• Iteration patterns
• Reversal and rotation
• Insertion and deletion within a fixed array

Practice

• Rotate an array right by k — Brain Station 23, with answer
• Reverse a string without library functions — Chaldal, with answer
• Sort by a given asc/desc criterion — Bevy Commerce

String Fundamentals

• Character encoding and representation
• Immutability and the cost of concatenation
• Common string operations

Practice

• Convert a numeric string to an integer — Chaldal, with answer
• Check whether a string is a palindrome — Chaldal, with answer
• Extract digits from a string — Chaldal, with answer
• Trim and collapse whitespace — Brain Station 23, with answer

Two-Pointer Technique

• Opposite-end pointers
• Fast and slow pointers
• Pair and triplet problems

Practice

• Two sum — bKash, with answer
• Pairs with a target sum in a doubly linked list — Therap, with answer

Sliding Window

• Fixed-size windows
• Variable-size windows
• Substring and subarray problems

Practice

• Find all anagram substrings — Chaldal, with answer
• Minimum window substring — Therap, with answer
• Nearby almost-duplicate pair — Kite Games, with answer

Prefix Sums

• Prefix sum arrays
• Range sum queries
• Difference arrays

Practice

• Range queries over an array — AppsCode
• Count values in range per query — Enosis
• Difference of odd- and even-indexed sums — Enosis
• Evaluate f(l, r) for many queries — Kite Games

Multidimensional Arrays

• 2D array traversal
• Matrix rotation and transposition
• Grid-based problems

Practice

• Rotate an n×n matrix 90° — Enosis, with answer
• Spiral matrix lookup — Chaldal, with answer

Linked Lists

Node structure, traversal, and basic insert/delete operations, then reversal, cycle detection, and building tree-like structures out of nodes.

Coverage: moderate

Resources · NeetCode — Linked List

Linked List Fundamentals

• Node structure and pointers
• Singly, doubly, and circular linked lists
• Comparison with arrays

Practice

• Array vs. linked list — Exabyting, with answer
• Advantages and disadvantages of linked lists — WellDev
• Which statement about a singly linked list is false — Brain Station 23
• Can binary search run on a sorted linked list — WellDev, with answer

Core Operations

• Traversal
• Insertion at head, tail, and middle
• Deletion
• Search

Practice

• Insert and delete in a doubly linked list — Shanghai BD
• Insertion and deletion in a circular list — WellDev
• Remove duplicates from a sorted list — bKash

Pointer Techniques

• Iterative and recursive reversal
• Fast and slow pointers
• Cycle detection
• Finding the middle node
• Nth node from the end

Practice

• Reverse a singly linked list — bKash, with answer
• Reverse every block of three nodes — Therap, with answer
• Remove the nth node from the end — Therap, with answer
• Nth from the end of a circular list — Brain Station 23, with answer
• Clone a list with random pointers — SRBD, with answer

Multi-List Problems

• Merging sorted lists
• Intersection of two lists
• Partitioning

Practice

• Merge two sorted linked lists — Therap, with answer

Stacks & Queues

What LIFO and FIFO mean, and the problems each is the right tool for — browser history, CPU scheduling, expression evaluation.

Coverage: moderate

Resources · NeetCode — Stack

Stack Fundamentals

• LIFO ordering
• Push, pop, and peek
• Array-based vs. linked-list-based implementation

Practice

• Stack, queue and priority queue — Exabyting, with answer
• Describe stacks and queues — WellDev
• Delete the middle element of a stack — WellDev

Stack Applications

• Expression notation (infix, prefix, postfix) and evaluation
• Balanced parentheses
• Undo history and browser navigation
• The function call stack

Practice

• Valid parentheses — bKash, with answer
• Convert infix to postfix — Brain Station 23
• Evaluate a postfix expression — National University
• Evaluate infix or postfix notation — Shanghai BD
• When is a stack the right choice — Brain Station 23

Queue Fundamentals

• FIFO ordering
• Enqueue and dequeue
• Circular queues
• Array-based vs. linked-list-based implementation

Practice

• Remaining capacity of a circular queue — Brain Station 23, with answer
• Deque operations — National University

Queue Variants & Applications

• Deque
• Priority queue
• CPU scheduling and buffering
• Monotonic stack and queue

Practice

• Build a stack out of a queue — WellDev, with answer
• A queue exposing its kth-last element — ShellBeeHaken

Trees & Binary Search Trees

Tree terminology and traversal order, binary search tree operations, tree properties (full/complete), and heaps as priority queues.

Coverage: rich

Resources · NeetCode — Trees & Heap/Priority Queue · VisuAlgo — tree visualisations

Tree Fundamentals

• Terminology: root, node, leaf, height, depth, degree
• Binary vs. n-ary trees
• Tree properties: full, complete, perfect, balanced
• Array and linked representations

Practice

• Full vs. complete binary tree — Brain Station 23
• Tree, binary tree and BST compared — Exabyting, with answer
• Build a tree from a list of nodes — Enosis
• Build a linked-node tree with left/right children — Enosis

Tree Traversal

• Inorder, preorder, and postorder
• Level-order traversal
• Recursive vs. iterative traversal

Practice

• Maximum depth of a binary tree — Chaldal, with answer
• Traverse a tree with a moving robot — Inverse AI
• Classify nodes from a parent/child table — Therap

Binary Search Trees

• BST ordering property
• Search, insertion, and deletion
• Degenerate trees and worst-case complexity
• Inorder successor and predecessor
• Lowest common ancestor

Practice

• Explain the BST property — Exabyting, with answer
• Binary tree vs. BST — Exabyting, with answer
• Insert a sorted array into a BST — Exabyting, with answer
• Search complexity in a balanced BST — Brain Station 23, with answer
• Lowest common ancestor in a BST — Brain Station 23, with answer

Balanced Trees

• Purpose of balancing
• Rotations
• AVL trees
• Red-black trees

Practice

• Operation complexity in a red-black tree — Enosis

Heaps & Priority Queues

• Min-heap and max-heap properties
• Array representation of a heap
• Heapify, insertion, and extraction
• Priority queue applications

Practice

• How a priority queue works internally — Enosis
• Ten smallest of a thousand unsorted numbers — Shanghai BD

Specialized Trees

• Trie (prefix tree)
• Segment tree
• Binary indexed tree (Fenwick tree)

Practice

• How a trie works, and implementing one — AppsCode
• Which structure suits a dictionary app — Brain Station 23
• Look-ups over a sorted word list — Therap, with answer

Graphs

Representation (adjacency list vs. matrix) and structural properties like bipartiteness. Traversal and shortest-path algorithms live under Graph Algorithms below.

Coverage: moderate

Resources · NeetCode — Graphs · VisuAlgo — graph structures

Graph Fundamentals

• Vertices and edges
• Directed vs. undirected graphs
• Weighted vs. unweighted graphs
• Degree, path, and cycle

Practice

• Key differences between a tree and a graph — Enosis

Graph Representation

• Adjacency matrix
• Adjacency list
• Edge list
• Space and time trade-offs between representations

Practice

• Adjacency list vs. adjacency matrix — Brain Station 23
• How to represent a graph in code — WellDev

Graph Properties

• Connectivity and connected components
• Trees as a special case of graphs
• Bipartite graphs
• Dense vs. sparse graphs
• Directed acyclic graphs

Practice

• Identify the non-bipartite graph — Brain Station 23, with answer
• Count connected components — RoBenDevs, with answer
• Count disjoint clusters of cities — IQVIA

Hashing (Hash Tables & Maps)

How hashing works (hash functions, collisions), hash tables and hash maps, and when to reach for one over a tree or array.

Coverage: thin

Resources · NeetCode — Arrays & Hashing

Hashing Fundamentals

• Hash functions and their properties
• Hash tables, hash maps, and hash sets
• Average vs. worst-case complexity

Practice

• What hashing is, and what a collision is — AppsCode
• map vs. unordered_map and their complexity — Exabyting, with answer

Collision Handling

• Separate chaining
• Open addressing (linear probing, quadratic probing, double hashing)
• Load factor and rehashing

Practice

• How collisions arise and are handled — AppsCode

Applications

• Frequency counting
• Deduplication and membership testing
• Caching and lookup tables
• Choosing a hash map over a tree or array

Practice

• Highest-frequency character in a string — ShopUp
• Sort elements by frequency, stable on ties — IQVIA
• Sort using a frequency count — IQVIA