A Technical Interview
1
Introduction
1.1
How to Use This Book
1.2
Problem Template
1.2.1
Problem Metadata
1.2.2
Description
1.2.3
Examples
1.2.4
Constraints
1.2.5
Solution
1.3
Glossary of Algorithm
1.3.1
Depth First Traversal
1.3.2
Breadth First Traversal
1.3.3
Topological Sort
1.3.4
Minimax
1.3.5
Recursion
1.3.6
Backtracking
1.3.7
Dynamic Programming
1.3.8
Memoization
1.3.9
Tabulation
1.3.10
Divide and Conquer
1.3.11
Binary Search Tree
1.3.12
Merge sort
1.3.13
Bubble sort
1.3.14
Insertion Sort
1.3.15
Quick Sort
1.3.16
Minimum Heap
1.3.17
Stack
1.3.18
Greedy
1.3.19
Two Pointer
1.3.20
Sliding Window
1.3.21
Hash Table
1.3.22
Binary Search
1.3.23
Sorting
1.3.24
Matrix Traversal
1.3.25
Matrix Manipulation
1.3.26
Array
1.3.27
Linked List
1.3.28
Queue
1.3.29
Trie
1.3.30
Bitwise Operations
1.3.31
Bit Manipulation
1.3.32
Simulation
1.3.33
Probability
1.3.34
Rejection Sampling
1.3.35
Reservoir Sampling
2
Common Strategies
2.1
Two Pointer
2.1.1
Core Concept
2.1.2
Common Patterns
2.1.3
Two Pointer vs Other Techniques
2.1.4
Common Pitfalls
2.1.5
Summary
2.2
Algorithm Selection: Greedy vs Dynamic Programming vs Backtracking
2.2.1
Core Differences
2.2.2
Key Insight: Local vs Global vs Exhaustive
2.2.3
When to Use Greedy
2.2.4
When to Use Dynamic Programming
2.2.5
When to Use Backtracking
2.2.6
The Critical Distinction: Same Problem, Different Questions
2.2.7
Hybrid Cases: DP with Path Reconstruction
2.2.8
Overlapping Subproblems: The Deciding Factor
2.2.9
Decision Tree
2.2.10
Common Mistakes
2.2.11
Summary Table: Which Algorithm for Which Problem?
2.2.12
Key Takeaway
2.3
Sorting Algorithms
2.3.1
Core Concepts
2.3.2
Bubble Sort
2.3.3
Insertion Sort
2.3.4
Merge Sort
2.3.5
Quick Sort
2.3.6
Topological Sort
2.3.7
When to Use Which Sorting Algorithm
2.4
Searching Algorithms
2.4.1
Binary Search
2.4.2
QuickSelect
3
Arrays
3.0.1
Iterating Combinations
3.0.2
N Sum Family Comparison
3.0.3
Greedy Array Patterns
3.1
Two Sums I
3.1.1
Problem Metadata
3.1.2
Description
3.1.3
Examples
3.1.4
Constraints
3.1.5
Solution - Hash Table Approach
3.1.6
Solution - Storing Difference
3.2
Median of Two Sorted Arrays
3.2.1
Problem Metadata
3.2.2
Description
3.2.3
Examples
3.2.4
Constraints
3.2.5
Solution - Binary Elimination (Optimal)
3.2.6
Solution - Two Heaps (Simpler but Suboptimal)
3.3
Container With Most Water
3.3.1
Problem Metadata
3.3.2
Description
3.3.3
Examples
3.3.4
Constraints
3.3.5
Solution - Two Pointers
3.4
Three Sum
3.4.1
Problem Metadata
3.4.2
Description
3.4.3
Examples
3.4.4
Constraints
3.4.5
Solution - Sort + Two Pointers
3.5
3 Sum Closest
3.5.1
Problem Metadata
3.5.2
Description
3.5.3
Examples
3.5.4
Constraints
3.5.5
Solution - Sort + Two Pointers
3.6
4Sum
3.6.1
Problem Metadata
3.6.2
Description
3.6.3
Examples
3.6.4
Constraints
3.6.5
Solution - Nested Two Pointers
3.7
Remove Duplicates from Sorted Array
3.7.1
Problem Metadata
3.7.2
Description
3.7.3
Examples
3.7.4
Constraints
3.7.5
Solution - Two Pointers
3.8
Search in Rotated Sorted Array
3.8.1
Problem Metadata
3.8.2
Description
3.8.3
Examples
3.8.4
Constraints
3.8.5
Solution - Modified Binary Search
3.9
Maximum Subarray
3.9.1
Problem Metadata
3.9.2
Description
3.9.3
Examples
3.9.4
Constraints
3.9.5
Solution - Kadane’s Algorithm
3.10
Merge Intervals
3.10.1
Problem Metadata
3.10.2
Description
3.10.3
Examples
3.10.4
Constraints
3.10.5
Solution - Sort then Merge
3.11
Insert Interval
3.11.1
Problem Metadata
3.11.2
Description
3.11.3
Examples
3.11.4
Constraints
3.11.5
Solution - Linear Merge
3.12
Plus One
3.12.1
Problem Metadata
3.12.2
Description
3.12.3
Examples
3.12.4
Constraints
3.12.5
Solution - Carry Propagation
3.13
Sort Colors
3.13.1
Problem Metadata
3.13.2
Description
3.13.3
Examples
3.13.4
Constraints
3.13.5
Follow-up
3.13.6
Solution - Two Pointers (Two Pass)
3.14
Best Time to Buy and Sell Stock
3.14.1
Problem Metadata
3.14.2
Description
3.14.3
Examples
3.14.4
Constraints
3.14.5
Solution - Track Min Price
3.15
Best Time to Buy and Sell Stock II
3.15.1
Problem Metadata
3.15.2
Description
3.15.3
Examples
3.15.4
Constraints
3.15.5
Solution - Sum Positive Differences
3.16
Gas Station
3.16.1
Problem Metadata
3.16.2
Description
3.16.3
Examples
3.16.4
Constraints
3.16.5
Solution - Greedy One Pass
3.17
Maximum Product Subarray
3.17.1
Problem Metadata
3.17.2
Description
3.17.3
Examples
3.17.4
Constraints
3.17.5
Solution - Track Max and Min Products
3.18
Two Sum II - Input Array Is Sorted
3.18.1
Problem Metadata
3.18.2
Description
3.18.3
Examples
3.18.4
Constraints
3.18.5
Solution - Two Pointers
3.18.6
Solution - Binary Search
3.19
Minimum Size Subarray Sum
3.19.1
Problem Metadata
3.19.2
Description
3.19.3
Examples
3.19.4
Constraints
3.19.5
Solution - Sliding Window
3.20
Product of Array Except Self
3.20.1
Problem Metadata
3.20.2
Description
3.20.3
Examples
3.20.4
Constraints
3.20.5
Follow-up
3.20.6
Solution - Prefix and Suffix Arrays
3.20.7
Solution - Space-Optimized (Follow-up)
3.21
Find the Duplicate Number
3.21.1
Problem Metadata
3.21.2
Description
3.21.3
Examples
3.21.4
Constraints
3.21.5
Follow-up
3.21.6
Solution - Floyd’s Cycle Detection (Tortoise and Hare)
3.22
Random Pick Index
3.22.1
Problem Metadata
3.22.2
Description
3.22.3
Examples
3.22.4
Constraints
3.22.5
Solution - Reservoir Sampling
3.22.6
Alternative Solution - Hash Map (Preprocessing)
3.22.7
Comparison of Solutions
3.23
Random Pick with Weight
3.23.1
Problem Metadata
3.23.2
Description
3.23.3
Examples
3.23.4
Constraints
3.23.5
Solution - Prefix Sum + Binary Search
3.24
Non-overlapping Intervals
3.24.1
Problem Metadata
3.24.2
Description
3.24.3
Examples
3.24.4
Constraints
3.24.5
Solution - Greedy by End Time
3.25
4Sum II
3.25.1
Problem Metadata
3.25.2
Description
3.25.3
Examples
3.25.4
Constraints
3.25.5
Solution - Hash Map Pair Sums
3.26
Binary Search
3.26.1
Problem Metadata
3.26.2
Description
3.26.3
Examples
3.26.4
Constraints
3.26.5
Solution - Binary Search (Recursive)
3.27
Maximize Distance to Closest Person
3.27.1
Problem Metadata
3.27.2
Description
3.27.3
Examples
3.27.4
Constraints
3.27.5
Solution - One-Pass Greedy
3.28
Hand of Straights
3.28.1
Problem Metadata
3.28.2
Description
3.28.3
Examples
3.28.4
Constraints
3.28.5
Solution - Greedy with Sorted TreeMap
3.28.6
Solution - Greedy with HashMap + Stream Sort
3.29
Koko Eating Bananas
3.29.1
Problem Metadata
3.29.2
Description
3.29.3
Examples
3.29.4
Constraints
3.29.5
Solution - Binary Search on Answer
3.30
Sort Array By Parity
3.30.1
Problem Metadata
3.30.2
Description
3.30.3
Examples
3.30.4
Constraints
3.30.5
Solution - Two Pointers
3.31
Interval List Intersections
3.31.1
Problem Metadata
3.31.2
Description
3.31.3
Examples
3.31.4
Constraints
3.31.5
Solution - Two Pointers
3.32
Find Common Characters
3.32.1
Problem Metadata
3.32.2
Description
3.32.3
Examples
3.32.4
Constraints
3.32.5
Solution - Frequency Intersection
3.33
Cutting Ribbons
3.33.1
Problem Metadata
3.33.2
Description
3.33.3
Examples
3.33.4
Constraints
3.33.5
Solution - Binary Search on Answer
3.34
Merge Triplets to Form Target Triplet
3.34.1
Problem Metadata
3.34.2
Description
3.34.3
Examples
3.34.4
Constraints
3.34.5
Solution - Greedy
3.35
Eliminate Maximum Number of Monsters
3.35.1
Problem Metadata
3.35.2
Description
3.35.3
Examples
3.35.4
Constraints
3.35.5
Solution 1
3.35.6
Notes
3.36
Number of Zero-Filled Subarrays
3.36.1
Problem Metadata
3.36.2
Description
3.36.3
Examples
3.36.4
Constraints
3.36.5
Solution - Triangular Number Formula
3.37
Divide Array Into Arrays With Max Difference
3.37.1
Problem Metadata
3.37.2
Description
3.37.3
Examples
3.37.4
Constraints
3.37.5
Solution
3.38
Minimum Operations to Make Binary Array Elements Equal to One I
3.38.1
Problem Metadata
3.38.2
Description
3.38.3
Examples
3.38.4
Constraints
3.38.5
Solution - Greedy Sequential Traversal
3.38.6
Java Code
3.39
Shortest Word Distance
3.39.1
Problem Metadata
3.39.2
Description
3.39.3
Examples
3.39.4
Constraints
3.39.5
Solution - Single Pass
3.40
Count Elements Greater Than Previous Average
3.40.1
Problem Metadata
3.40.2
Description
3.40.3
Examples
3.40.4
Constraints
3.40.5
Solution - Running Sum with Floating Point Average
3.41
Count Number Pairs
3.41.1
Problem Metadata
3.41.2
Description
3.41.3
Examples
3.41.4
Input Format
3.41.5
Output Format
3.41.6
Constraints
3.41.7
Solution - Two Pointers with Sorted Array Optimization
3.41.8
Solution - Optimal Two Pointers (Linear Time)
3.42
Merge and Sort Intervals (HackerRank)
3.42.1
Problem Metadata
3.42.2
Description
3.42.3
Examples
3.42.4
Input Format
3.42.5
Constraints
3.42.6
Solution
3.43
Merge and Sort Intervals with Arrays
3.43.1
Problem Metadata
3.43.2
Description
3.43.3
Examples
3.43.4
Input Format
3.43.5
Constraints
3.43.6
Solution
3.43.7
Solution
3.44
Two Sum II - Boolean
3.44.1
Problem Metadata
3.44.2
Description
3.44.3
Examples
3.44.4
Constraints
3.44.5
Solution - Hash Set
3.45
Two Sum V
3.45.1
Problem Metadata
3.45.2
Description
3.45.3
Examples
3.45.4
Constraints
3.45.5
Solution - Two Pointers
3.46
Max Gain
3.46.1
Problem Metadata
3.46.2
Description
3.46.3
Examples
3.46.4
Constraints
3.46.5
Solution - One-Pass Greedy
3.47
Retrieve Elements K Times
3.47.1
Problem Metadata
3.47.2
Description
3.47.3
Examples
3.47.4
Constraints
3.47.5
Solution - Hash Map Counting
3.48
Maximum Number of Repetitions
3.48.1
Problem Metadata
3.48.2
Description
3.48.3
Examples
3.48.4
Constraints
3.48.5
Solution - In-place Counting
3.49
Selection Sort Array
3.49.1
Problem Metadata
3.49.2
Description
3.49.3
Examples
3.49.4
Constraints
3.49.5
Solution - Iterative Selection
3.50
Quick Sort Array
3.50.1
Problem Metadata
3.50.2
Description
3.50.3
Examples
3.50.4
Constraints
3.50.5
Solution - Lomuto Partitioning
4
Matrix
4.0.1
Definition and Properties
4.0.2
Time and Space Complexity Considerations
4.0.3
Traversal Patterns
4.0.4
Transformation Operations
4.0.5
Algorithmic Techniques
4.1
Valid Sudoku
4.1.1
Problem Metadata
4.1.2
Description
4.1.3
Examples
4.1.4
Constraints
4.1.5
Solution 1 - Three Separate Passes (Brute Force)
4.1.6
Solution 2 - Single Pass with String Keys (Optimized)
4.2
Rotate Image
4.2.1
Problem Metadata
4.2.2
Description
4.2.3
Examples
4.2.4
Constraints
4.2.5
Solution - Transpose + Reverse
4.3
Spiral Matrix
4.3.1
Problem Metadata
4.3.2
Description
4.3.3
Examples
4.3.4
Constraints
4.3.5
Solution - Boundary Simulation
4.4
Set Matrix Zeroes
4.4.1
Problem Metadata
4.4.2
Description
4.4.3
Examples
4.4.4
Constraints
4.4.5
Follow-up
4.4.6
Solution - First Row/Column as Markers
4.5
Search a 2D Matrix
4.5.1
Problem Metadata
4.5.2
Description
4.5.3
Examples
4.5.4
Constraints
4.5.5
Solution - Treat as 1D
4.5.6
Solution 2 - Row-First Linear Search
4.6
Surrounded Regions
4.6.1
Problem Metadata
4.6.2
Description
4.6.3
Examples
4.6.4
Constraints
4.6.5
Solution - Mark Border Regions
4.6.6
Solution 2 - BFS Approach
4.7
Number of Islands
4.7.1
Problem Metadata
4.7.2
Description
4.7.3
Examples
4.7.4
Constraints
4.7.5
Solution - Flood Fill
4.8
Search a 2D Matrix II
4.8.1
Problem Metadata
4.8.2
Description
4.8.3
Examples
4.8.4
Constraints
4.8.5
Solution - Staircase Search
4.9
Walls and Gates
4.9.1
Problem Metadata
4.9.2
Description
4.9.3
Examples
4.9.4
Constraints
4.9.5
Solution - Multi-Source BFS
4.10
Pacific Atlantic Water Flow
4.10.1
Problem Metadata
4.10.2
Description
4.10.3
Examples
4.10.4
Constraints
4.10.5
Solution - DFS from Ocean Borders
4.11
Best Meeting Point
4.11.1
Problem Metadata
4.11.2
Description
4.11.3
Examples
4.11.4
Constraints
4.11.5
Solution - Median Trick
4.12
Design Tic-Tac-Toe
4.12.1
Problem Metadata
4.12.2
Description
4.12.3
Examples
4.12.4
Constraints
4.12.5
Solution - Running Counts
4.13
Battleships in a Board
4.13.1
Problem Metadata
4.13.2
Description
4.13.3
Examples
4.13.4
Constraints
4.13.5
Follow-up
4.13.6
Solution - Top-Left Corner Counting
4.14
01 Matrix
4.14.1
Problem Metadata
4.14.2
Description
4.14.3
Examples
4.14.4
Constraints
4.14.5
Solution 1 - Multi-Source BFS (Matrix Modification)
4.14.6
Solution 2 - Multi-Source BFS (Visited Array - Standard)
4.15
Brick Wall
4.15.1
Problem Metadata
4.15.2
Description
4.15.3
Examples
4.15.4
Constraints
4.15.5
Solution - Hash Map with Prefix Sum
4.16
Rotting Oranges
4.16.1
Problem Metadata
4.16.2
Description
4.16.3
Examples
4.16.4
Constraints
4.16.5
Solution - Multi-Source BFS
4.17
Detect Squares
4.17.1
Problem Metadata
4.17.2
Description
4.17.3
Examples
4.17.4
Constraints
4.17.5
Solution - Hash Map with Frequency Counting
5
Tree
5.0.1
Tree Representation
5.0.2
Breadth First Traversal
5.0.3
Depth First Traversal
5.0.4
Pre-Order Traversal
5.0.5
In-Order Traversal
5.0.6
Post-Order Traversal
5.0.7
Selection Strategy
5.0.8
Binary Search Tree
5.1
Binary Tree Inorder Traversal
5.1.1
Problem Metadata
5.1.2
Description
5.1.3
Examples
5.1.4
Constraints
5.1.5
Solution - Iterative Stack
5.1.6
Solution - Recursive
5.2
Validate Binary Search Tree
5.2.1
Problem Metadata
5.2.2
Description
5.2.3
Examples
5.2.4
Constraints
5.2.5
Solution - Inorder Bounds
5.3
Binary Tree Zigzag Level Order Traversal
5.3.1
Problem Metadata
5.3.2
Description
5.3.3
Examples
5.3.4
Constraints
5.3.5
Solution - BFS with Direction Flag
5.4
Maximum Depth of Binary Tree
5.4.1
Problem Metadata
5.4.2
Description
5.4.3
Examples
5.4.4
Constraints
5.4.5
Solution - DFS Recursion
5.5
Construct Binary Tree from Preorder and Inorder Traversal
5.5.1
Problem Metadata
5.5.2
Description
5.5.3
Examples
5.5.4
Constraints
5.5.5
Solution - Hash Map with Divide and Conquer
5.6
Binary Tree Level Order Traversal II
5.6.1
Problem Metadata
5.6.2
Description
5.6.3
Examples
5.6.4
Constraints
5.6.5
Solution - Reverse BFS
5.7
Convert Sorted Array to BST
5.7.1
Problem Metadata
5.7.2
Description
5.7.3
Examples
5.7.4
Constraints
5.7.5
Solution - Divide and Conquer
5.8
Balanced Binary Tree
5.8.1
Problem Metadata
5.8.2
Description
5.8.3
Examples
5.8.4
Constraints
5.8.5
Solution - Recursive DFS
5.9
Binary Tree Level Order Traversal
5.9.1
Problem Metadata
5.9.2
Description
5.9.3
Examples
5.9.4
Constraints
5.9.5
Solution - BFS with Two Queues
5.9.6
Solution - DFS
5.10
Minimum Depth of Binary Tree
5.10.1
Problem Metadata
5.10.2
Description
5.10.3
Solution - DFS
5.11
Path Sum
5.11.1
Problem Metadata
5.11.2
Description
5.11.3
Examples
5.11.4
Constraints
5.11.5
Solution - DFS with Running Sum
5.12
Path Sum II
5.12.1
Problem Metadata
5.12.2
Description
5.12.3
Solution - Backtracking
5.13
Populating Next Right Pointers in Each Node
5.13.1
Problem Metadata
5.13.2
Description
5.13.3
Solution - Level Traversal
5.14
Binary Tree Preorder Traversal
5.14.1
Problem Metadata
5.14.2
Description
5.14.3
Solution - Iterative Stack
5.14.4
Solution - Recursive
5.15
Binary Tree Postorder Traversal
5.15.1
Problem Metadata
5.15.2
Description
5.15.3
Solution - Iterative Stack
5.15.4
Solution - Recursive
5.16
Implement Trie (Prefix Tree)
5.16.1
Problem Metadata
5.16.2
Description
5.16.3
Examples
5.16.4
Constraints
5.16.5
Solution - TrieNode with HashMap
5.16.6
Solution - Array-Based TrieNode
5.17
Kth Smallest Element in a BST
5.17.1
Problem Metadata
5.17.2
Description
5.17.3
Examples
5.17.4
Constraints
5.17.5
Solution - In-Order Traversal (Recursive)
5.17.6
Solution - Iterative with Stack
5.18
Lowest Common Ancestor of a Binary Search Tree
5.18.1
Problem Metadata
5.18.2
Description
5.18.3
Examples
5.18.4
Constraints
5.18.5
Solution - DFS with Ancestor Checking
5.18.6
Solution - BST Properties (Optimal)
5.19
Two Sum IV - Input is a BST
5.19.1
Problem Metadata
5.19.2
Description
5.19.3
Examples
5.19.4
Constraints
5.19.5
Solution - DFS + HashSet
5.20
Lowest Common Ancestor of a Binary Tree
5.20.1
Problem Metadata
5.20.2
Description
5.20.3
Examples
5.20.4
Constraints
5.20.5
Solution 1 - DFS with Ancestor Checking
5.20.6
Solution 2 - Optimized Post-Order DFS
5.21
Binary Tree Upside Down
5.21.1
Problem Metadata
5.21.2
Description
5.21.3
Solution - Recursive Rotation
5.22
Count Univalue Subtrees
5.22.1
Problem Metadata
5.22.2
Description
5.22.3
Solution - DFS
5.23
Inorder Successor in BST
5.23.1
Problem Metadata
5.23.2
Description
5.23.3
Solution - BST Properties
5.24
Serialize and Deserialize Binary Tree
5.24.1
Problem Metadata
5.24.2
Description
5.24.3
Examples
5.24.4
Constraints
5.24.5
Solution - DFS Preorder Traversal
5.24.6
Solution - BFS Level-Order Traversal
5.25
Binary Tree Longest Consecutive Sequence
5.25.1
Problem Metadata
5.25.2
Description
5.25.3
Solution - DFS Tracking
5.26
Find Leaves of Binary Tree
5.26.1
Problem Metadata
5.26.2
Description
5.26.3
Solution - Height DFS
5.27
Path Sum III
5.27.1
Problem Metadata
5.27.2
Description
5.27.3
Solution - Prefix Sum DFS
5.28
Count Good Nodes in Binary Tree
5.28.1
Problem Metadata
5.28.2
Description
5.28.3
Examples
5.28.4
Constraints
5.28.5
Solution - DFS with Path Maximum
5.28.6
Solution - BFS with Node-Max Wrapper
5.28.7
BFS vs DFS Comparison
5.29
Subtree of Another Tree
5.29.1
Problem Metadata
5.29.2
Description
5.29.3
Examples
5.29.4
Constraints
5.29.5
Solution - DFS with Tree Comparison
5.30
Diameter of Binary Tree
5.30.1
Problem Metadata
5.30.2
Description
5.30.3
Solution - DFS
5.31
Height of Binary Search Tree
5.31.1
Problem Metadata
5.31.2
Description
5.31.3
Examples
5.31.4
Input Format
5.31.5
Constraints
5.31.6
Output Format
5.31.7
Solution - Recursive DFS
5.32
Binary Tree Serialization
5.32.1
Problem Metadata
5.32.2
Description
5.32.3
Examples
5.32.4
Constraints
5.32.5
Solution - Preorder with Null Markers
5.33
Fill in the Ancestors of the Node
5.33.1
Problem Metadata
5.33.2
Description
5.33.3
Examples
5.33.4
Solution - DFS Path Building
5.34
Find the k-th Largest Node in a BST
5.34.1
Problem Metadata
5.34.2
Description
5.34.3
Examples
5.34.4
Constraints
5.34.5
Solution - Reverse Inorder
6
Graph
6.0.1
Undirected Graphs
6.0.2
Directed Acyclic Graph
6.0.3
Weighted Graphs
6.1
Clone Graph
6.1.1
Problem Metadata
6.1.2
Description
6.1.3
Examples
6.1.4
Constraints
6.1.5
Solution - DFS with Map
6.1.6
Solution - BFS with Map
6.2
Course Schedule
6.2.1
Problem Metadata
6.2.2
Description
6.2.3
Examples
6.2.4
Constraints
6.2.5
Solution - Kahn’s Algorithm
6.2.6
Solution - DFS with Color Marking
6.2.7
Solution - DFS with Recursion Stack
6.2.8
Solution - DFS with Post-order Visiting
6.3
Course Schedule II
6.3.1
Problem Metadata
6.3.2
Description
6.3.3
Examples
6.3.4
Constraints
6.3.5
Solution - BFS Order
6.4
Graph Validate Tree
6.4.1
Problem Metadata
6.4.2
Description
6.4.3
Examples
6.4.4
Constraints
6.4.5
Solution - Union Find
6.4.6
Solution - DFS with Parent Tracking
6.4.7
Solution - BFS with Parent Tracking
6.5
Alien Dictionary
6.5.1
Problem Metadata
6.5.2
Description
6.5.3
Examples
6.5.4
Constraints
6.5.5
Solution - Topological Sort with DFS
6.6
Number of Connected Components in an Undirected Graph
6.6.1
Problem Metadata
6.6.2
Description
6.6.3
Examples
6.6.4
Constraints
6.6.5
Solution - DFS Traversal
6.6.6
Solution - BFS Traversal
6.6.7
Solution - Union Find
6.7
Accounts Merge
6.7.1
Problem Metadata
6.7.2
Description
6.7.3
Examples
6.7.4
Constraints
6.7.5
Solution - Union Find
6.7.6
Solution - DFS
6.8
Network Delay Time
6.8.1
Problem Metadata
6.8.2
Description
6.8.3
Examples
6.8.4
Constraints
6.8.5
Solution - Dijkstra’s Algorithm
6.9
Distance of Nearest Cell Having 1
6.9.1
Problem Metadata
6.9.2
Description
6.9.3
Solution - Multi-source BFS
6.10
Graph Serialization
6.10.1
Problem Metadata
6.10.2
Description
6.10.3
Solution - BFS
6.11
Hardware Build Feasibility
6.11.1
Problem Metadata
6.11.2
Description
6.11.3
Examples
6.11.4
Constraints
6.11.5
Solution - Topological Sort (Kahn’s BFS)
6.11.6
Solution - DFS with State Tracking
7
Linked List
7.0.1
Fast and Slow Pointer Technique
7.0.2
Reversal Techniques
7.0.3
Dummy Head Pattern
7.0.4
Two-Pointer Technique
7.0.5
Merge Techniques
7.0.6
In-Place Transformation
7.0.7
Common Patterns Summary
7.0.8
Problem-Solving Checklist
7.1
Add Two Numbers
7.1.1
Problem Metadata
7.1.2
Description
7.1.3
Examples
7.1.4
Constraints
7.1.5
Solution - Iterative Carry Addition
7.2
Remove Nth Node From End of List
7.2.1
Problem Metadata
7.2.2
Description
7.2.3
Examples
7.2.4
Constraints
7.2.5
Solution - Two Pointers with Gap
7.3
Merge Two Sorted Lists
7.3.1
Problem Metadata
7.3.2
Description
7.3.3
Examples
7.3.4
Constraints
7.3.5
Solution - Iterative Merge
7.4
Merge k Sorted Lists
7.4.1
Problem Metadata
7.4.2
Description
7.4.3
Examples
7.4.4
Constraints
7.4.5
Solution - Min-Heap
7.5
Reverse Nodes in k-Group
7.5.1
Problem Metadata
7.5.2
Description
7.5.3
Examples
7.5.4
Constraints
7.5.5
Solution - Iterative Group Reversal
7.6
Remove Duplicates from Sorted List
7.6.1
Problem Metadata
7.6.2
Description
7.6.3
Examples
7.6.4
Constraints
7.6.5
Solution - In-Place Skip
7.7
Reverse Linked List II
7.7.1
Problem Metadata
7.7.2
Description
7.7.3
Examples
7.7.4
Constraints
7.7.5
Solution - Head Insertion
7.8
Copy List with Random Pointer
7.8.1
Problem Metadata
7.8.2
Description
7.8.3
Examples
7.8.4
Constraints
7.8.5
Solution - HashMap (Two-Pass)
7.8.6
Solution - Interleaving Nodes (Space Optimized)
7.9
Linked List Cycle
7.9.1
Problem Metadata
7.9.2
Description
7.9.3
Solution - Floyd’s Cycle Detection
7.10
Linked List Cycle II
7.10.1
Problem Metadata
7.10.2
Description
7.10.3
Solution - Floyd’s Cycle Detection with Entry Point
7.11
Reorder List
7.11.1
Problem Metadata
7.11.2
Description
7.11.3
Solution - Find Middle, Reverse, Merge
7.12
Insertion Sort List
7.12.1
Problem Metadata
7.12.2
Description
7.12.3
Examples
7.12.4
Constraints
7.12.5
Solution - Dummy Head Insertion
7.13
Sort List
7.13.1
Problem Metadata
7.13.2
Description
7.13.3
Examples
7.13.4
Constraints
7.13.5
Solution - Merge Sort on Linked List
7.14
Intersection of Two Linked Lists
7.14.1
Problem Metadata
7.14.2
Solution - Two Pointers
7.15
Reverse Linked List
7.15.1
Problem Metadata
7.15.2
Description
7.15.3
Solution - Iterative Two Pointers
7.15.4
Solution - Recursive
7.16
Palindrome Linked List
7.16.1
Problem Metadata
7.16.2
Solution - Two Pointers
7.17
Odd Even Linked List
7.17.1
Problem Metadata
7.17.2
Description
7.17.3
Solution - Two Pointers
7.18
Merge In Between Linked Lists
7.18.1
Problem Metadata
7.18.2
Description
7.18.3
Examples
7.18.4
Constraints
7.18.5
Solution - Pointer Manipulation
7.19
One-Pass Removal of k-th Node from End
7.19.1
Problem Metadata
7.19.2
Description
7.19.3
Examples
7.19.4
Input Format
7.19.5
Constraints
7.19.6
Output Format
7.19.7
Sample Input 0
7.19.8
Sample Output 0
7.19.9
Sample Input 1
7.19.10
Sample Output 1
7.19.11
Solution - Three Pointers with Forward Search
7.20
Reverse Even-Indexed Nodes and Append
7.20.1
Problem Metadata
7.20.2
Description
7.20.3
Examples
7.20.4
Input Format
7.20.5
Constraints
7.20.6
Output Format
7.20.7
Sample Input 0
7.20.8
Sample Output 0
7.20.9
Sample Input 1
7.20.10
Sample Output 1
7.20.11
Solution - Extract, Reverse, and Append
7.21
Insert Node at Position in Doubly Linked List
7.21.1
Problem Metadata
7.21.2
Description
8
Stack and Queue
8.0.1
Stack Fundamentals
8.0.2
Monotonic Stack Pattern
8.0.3
Parentheses and Bracket Matching
8.0.4
Stack-Based State Tracking
8.0.5
Queue Fundamentals
8.0.6
Implementing Queue Using Stacks
8.0.7
Queue-Based Simulation
8.0.8
Stack vs Queue Decision Guide
8.0.9
Common Stack/Queue Patterns Summary
8.0.10
Problem-Solving Checklist
8.1
Longest Valid Parentheses
8.1.1
Problem Metadata
8.1.2
Description
8.1.3
Examples
8.1.4
Constraints
8.1.5
Solution - Stack
8.2
Evaluate Reverse Polish Notation
8.2.1
Problem Metadata
8.2.2
Description
8.2.3
Examples
8.2.4
Constraints
8.2.5
Solution - Stack
8.3
Min Stack
8.3.1
Problem Metadata
8.3.2
Description
8.3.3
Examples
8.3.4
Constraints
8.3.5
Solution - Single Stack with Paired Values
8.4
Implement Queue using Stacks
8.4.1
Problem Metadata
8.4.2
Description
8.4.3
Examples
8.4.4
Constraints
8.4.5
Solution - Two Stacks with Lazy Transfer
8.4.6
Related Problems
8.5
Task Scheduler
8.5.1
Problem Metadata
8.5.2
Description
8.5.3
Examples
8.5.4
Constraints
8.5.5
Solution - Mathematical Formula
8.5.6
Solution 2 - Greedy Simulation with Max Heap
8.6
Daily Temperatures
8.6.1
Problem Metadata
8.6.2
Description
8.6.3
Examples
8.6.4
Constraints
8.6.5
Solution - Monotonic Decreasing Stack
8.7
Car Fleet
8.7.1
Problem Metadata
8.7.2
Description
8.7.3
Examples
8.7.4
Constraints
8.7.5
Solution - Stack with Sorting
8.8
Maximum Score From Removing Substrings
8.8.1
Problem Metadata
8.8.2
Description
8.8.3
Examples
8.8.4
Constraints
8.8.5
Solution - Greedy with Stack
8.9
Validate Properly Nested Brackets
8.9.1
Metadata
8.9.2
Description
8.9.3
Walkthrough
8.9.4
Analysis
8.9.5
Implementation Steps
8.9.6
Java Code
8.10
Next Greater Element with Position Offset
8.10.1
Metadata
8.10.2
Description
8.10.3
Walkthrough
8.10.4
Analysis
8.10.5
Implementation Steps
8.10.6
Java Code
8.11
Lock-Free Stack Using Linked List (CAS)
8.11.1
Problem Metadata
8.11.2
Description
8.11.3
Examples
8.11.4
Constraints
8.11.5
Solution - Linked List Head as Top
9
Heap
9.0.1
Overview
9.0.2
Core Operations
9.0.3
Implementation - Golang
9.0.4
Implementation - Java
9.0.5
Common Patterns
9.0.6
Min Heap vs Max Heap Comparison
9.1
Find k-th Largest Element in an Array
9.1.1
Problem Metadata
9.1.2
Description
9.1.3
Examples
9.1.4
Constraints
9.1.5
Solution - Size-k Min Heap
9.2
Meeting Rooms II
9.2.1
Problem Metadata
9.2.2
Description
9.2.3
Examples
9.2.4
Constraints
9.2.5
Solution - Two-Pointer Sweep
9.2.6
Solution - Min-Heap
9.3
Find Median from Data Stream
9.3.1
Problem Metadata
9.3.2
Description
9.3.3
Examples
9.3.4
Constraints
9.3.5
Solution - Two Heaps
9.4
Top K Frequent Elements
9.4.1
Problem Metadata
9.4.2
Description
9.4.3
Examples
9.4.4
Constraints
9.4.5
Solution - Min-Heap Approach
9.4.6
Solution - Sorting with Stream API
9.4.7
Solution - QuickSelect (Optimal)
9.5
K Closest Points to Origin
9.5.1
Problem Metadata
9.5.2
Description
9.5.3
Examples
9.5.4
Constraints
9.5.5
Solution - Max Heap
9.5.6
Solution - Sort + Stream API
9.5.7
Solution - QuickSelect
9.6
Last Stone Weight
9.6.1
Problem Metadata
9.6.2
Description
9.6.3
Examples
9.6.4
Constraints
9.6.5
Solution - Max Heap
9.7
Top K Frequent Events with Order Preservation (HackerRank)
9.7.1
Problem Metadata
9.7.2
Description
9.7.3
Examples
9.7.4
Input Format
9.7.5
Output Format
9.7.6
Constraints
9.7.7
Solution
9.8
Merge K Sorted Arrays
9.8.1
Problem Metadata
9.8.2
Description
9.8.3
Examples
9.8.4
Constraints
9.8.5
Solution - Min Heap of Array Entries
9.9
Top K Elements
9.9.1
Problem Metadata
9.9.2
Description
9.9.3
Examples
9.9.4
Constraints
9.9.5
Solution 1 - Sort Then Slice
9.9.6
Solution 2 - Partial Bubble (k Passes)
9.9.7
Solution 3 - Min Heap of Size k
9.10
VIP Customer Scheduler
9.10.1
Metadata
9.10.2
Description
9.10.3
Walkthrough
9.10.4
Analysis
9.10.5
Implementation Steps
9.10.6
Java Code
9.10.7
Key Insights
10
String Manipulation
10.0.1
Sliding Window Pattern
10.0.2
Two-Pointer Technique
10.0.3
Character Frequency with HashMap
10.0.4
Anagram Detection Techniques
10.0.5
String Building and Concatenation
10.0.6
String Hashing
10.0.7
Common String Patterns Summary
10.0.8
Problem-Solving Checklist
10.1
Longest Substring Without Repeating Characters
10.1.1
Problem Metadata
10.1.2
Description
10.1.3
Examples
10.1.4
Constraints
10.1.5
Solution - Sliding Window Set
10.2
String to Integer (atoi)
10.2.1
Problem Metadata
10.2.2
Description
10.2.3
Examples
10.2.4
Constraints
10.2.5
Solution - Character-by-Character Parsing
10.3
Longest Common Prefix
10.3.1
Problem Metadata
10.3.2
Description
10.3.3
Examples
10.3.4
Constraints
10.3.5
Solution - Column Scan
10.4
Group Anagrams
10.4.1
Problem Metadata
10.4.2
Description
10.4.3
Examples
10.4.4
Constraints
10.4.5
Solution - Hash Signature Map
10.5
Word Ladder
10.5.1
Problem Metadata
10.5.2
Description
10.5.3
Examples
10.5.4
Constraints
10.5.5
Solution - BFS Over Word Mutations
10.6
Design Add and Search Words Data Structure
10.6.1
Problem Metadata
10.6.2
Description
10.6.3
Examples
10.6.4
Constraints
10.6.5
Solution - Trie with DFS
10.7
Encode and Decode Strings
10.7.1
Problem Metadata
10.7.2
Description
10.7.3
Examples
10.7.4
Constraints
10.7.5
Solution - Length Prefix Encoding
10.8
Ransom Note
10.8.1
Problem Metadata
10.8.2
Description
10.8.3
Examples
10.8.4
Constraints
10.8.5
Solution - Frequency Counting
10.9
Longest Palindrome
10.9.1
Problem Metadata
10.9.2
Description
10.9.3
Examples
10.9.4
Constraints
10.9.5
Solution - Greedy Frequency Counting
10.10
Longest Repeating Character Replacement
10.10.1
Problem Metadata
10.10.2
Description
10.10.3
Examples
10.10.4
Constraints
10.10.5
Solution - Sliding Window
10.11
Find All Anagrams in a String
10.11.1
Problem Metadata
10.11.2
Description
10.11.3
Examples
10.11.4
Constraints
10.11.5
Solution 1 - Brute Force with Frequency Map
10.11.6
Solution 2 - Sliding Window with Frequency Map
10.12
Permutation in String
10.12.1
Problem Metadata
10.12.2
Description
10.12.3
Examples
10.12.4
Constraints
10.12.5
Solution 1 - Brute Force with Frequency Map
10.12.6
Solution 2 - Sliding Window with Frequency Map
10.12.7
Solution Comparison
10.13
Valid Palindrome II
10.13.1
Problem Metadata
10.13.2
Description
10.13.3
Examples
10.13.4
Constraints
10.13.5
Solution - Two Pointers with One Skip Allowed
10.14
Sort Characters By Frequency
10.14.1
Problem Metadata
10.14.2
Description
10.14.3
Examples
10.14.4
Constraints
10.14.5
Solution - Frequency Map with Stream Sorting
10.15
Verifying an Alien Dictionary
10.15.1
Problem Metadata
10.15.2
Description
10.15.3
Examples
10.15.4
Constraints
10.15.5
Solution - Pairwise Comparison with Rank Map
10.16
Minimum Number of Steps to Make Two Strings Anagram
10.16.1
Problem Metadata
10.16.2
Description
10.16.3
Examples
10.16.4
Constraints
10.16.5
Solution
10.17
Number of Substrings Containing All Three Characters
10.17.1
Problem Metadata
10.17.2
Description
10.17.3
Examples
10.17.4
Constraints
10.17.5
Solution - Sliding Window
10.18
Check Palindrome by Filtering Non-Letters
10.18.1
Problem Metadata
10.18.2
Description
10.18.3
Examples
10.18.4
Constraints
10.18.5
Solution - Two Pointers with Filtering
10.19
Max Unique Substring Length in a Session
10.19.1
Problem Metadata
10.19.2
Description
10.19.3
Examples
10.19.4
Constraints
10.19.5
Solution - Split Sessions and Sliding Window
10.20
Binary Representation
10.20.1
Problem Metadata
10.20.2
Description
10.20.3
Examples
10.20.4
Constraints
10.20.5
Solution - Iterative Division
10.21
First Non-Repeated Character
10.21.1
Problem Metadata
10.21.2
Description
10.21.3
Examples
10.21.4
Constraints
10.21.5
Solution - Frequency Counting
10.22
Insert Stars
10.22.1
Problem Metadata
10.22.2
Description
10.22.3
Examples
10.22.4
Constraints
10.22.5
Solution - Recursive Pair Expansion
11
Math
11.0.1
Bit Manipulation
11.0.2
Digit Extraction and Manipulation
11.0.3
Fast Exponentiation
11.0.4
Number Theory
11.0.5
Probability and Rejection Sampling
11.1
Reverse Integer
11.1.1
Problem Metadata
11.1.2
Description
11.1.3
Examples
11.1.4
Constraints
11.1.5
Solution - Digit Extraction with Overflow Detection
11.2
Number of 1 Bits
11.2.1
Problem Metadata
11.2.2
Description
11.2.3
Examples
11.2.4
Constraints
11.2.5
Solution 1 - Digit Extraction with Modulo
11.2.6
Solution 2 - Brian Kernighan’s Algorithm
11.3
Pow(x, n)
11.3.1
Problem Metadata
11.3.2
Description
11.3.3
Examples
11.3.4
Constraints
11.3.5
Solution - Fast Exponentiation
11.4
Single Number
11.4.1
Problem Metadata
11.4.2
Description
11.4.3
Examples
11.4.4
Constraints
11.4.5
Solution 1 - HashSet
11.4.6
Solution 2 - XOR Bit Manipulation (Optimal)
11.5
Reverse Bits
11.5.1
Problem Metadata
11.5.2
Description
11.5.3
Examples
11.5.4
Constraints
11.5.5
Follow-up
11.5.6
Solution 1 - String Reversal
11.5.7
Solution 2 - Bit-by-Bit Reversal (Optimal)
11.6
Happy Number
11.6.1
Problem Metadata
11.6.2
Description
11.6.3
Examples
11.6.4
Constraints
11.6.5
Solution 1 - Hash Set Cycle Detection
11.6.6
Solution 2 - Floyd’s Cycle Detection (Two Pointers)
11.7
Count Primes
11.7.1
Problem Metadata
11.7.2
Description
11.7.3
Examples
11.7.4
Constraints
11.7.5
Solution - Sieve of Eratosthenes
11.8
Sum of Two Integers
11.8.1
Problem Metadata
11.8.2
Description
11.8.3
Examples
11.8.4
Constraints
11.8.5
Solution - Bitwise Addition
11.9
Implement Rand10() Using Rand7()
11.9.1
Problem Metadata
11.9.2
Description
11.9.3
Examples
11.9.4
Constraints
11.9.5
Follow-up
11.9.6
Solution - Rejection Sampling
11.10
Power of Two
11.10.1
Problem Metadata
11.10.2
Description
11.10.3
Examples
11.10.4
Constraints
11.10.5
Solution 1 - Recursive Halving
11.10.6
Solution 2 - Bitwise Trick
12
Interactive Problems
12.1
First Bad Version
12.1.1
Problem Metadata
12.1.2
Description
12.1.3
Examples
12.1.4
Constraints
12.1.5
Solution - Binary Search
12.2
Guess the Word
12.2.1
Problem Metadata
12.2.2
Description
12.2.3
Examples
12.2.4
Constraints
12.2.5
Solution - Minimax Filtering
13
Advanced Data Structure
13.1
Design LRU Cache
13.1.1
Problem Metadata
13.1.2
Description
13.1.3
Examples
13.1.4
Constraints
13.1.5
Solution 1 - Hash Map + Doubly Linked List
13.1.6
Solution 2 - LinkedHashMap
13.2
Design Twitter
13.2.1
Problem Metadata
13.2.2
Description
13.2.3
Examples
13.2.4
Constraints
13.2.5
Solution 1 - Min-Heap of Size 10 (Per-User Bucket)
13.2.6
Solution 2 - k-way Merge (Max-Heap with Lazy Loading)
13.3
Design HashSet
13.3.1
Problem Metadata
13.3.2
Description
13.3.3
Examples
13.3.4
Constraints
13.3.5
Solution - Separate Chaining Buckets
13.4
Design HashMap
13.4.1
Problem Metadata
13.4.2
Description
13.4.3
Examples
13.4.4
Constraints
13.4.5
Solution - Linked List Buckets
13.5
My Calendar I
13.5.1
Problem Metadata
13.5.2
Description
13.5.3
Examples
13.5.4
Constraints
13.5.5
Solution - Brute Force Interval Scan
13.5.6
Solution - TreeMap Boundary Search
13.6
Time Based Key-Value Store
13.6.1
Problem Metadata
13.6.2
Description
13.6.3
Examples
13.6.4
Constraints
13.6.5
Solution 1 - Hash Map with ArrayList + Binary Search
13.6.6
Solution 2 - Hash Map with TreeMap
13.6.7
Solution 3 - ArrayList with Binary Insertion (For Non-Increasing Timestamps)
13.7
Simple Bank System
13.7.1
Problem Metadata
13.7.2
Description
13.7.3
Examples
13.7.4
Constraints
13.7.5
Solution - Array-Based Account Storage
13.8
Implement Queue
13.8.1
Problem Metadata
13.8.2
Description
13.8.3
Examples
13.8.4
Constraints
13.8.5
Solution 1 - Circular Array
13.8.6
Solution 2 - Linked List
13.8.7
Solution 3 - Two Stacks
13.8.8
Related Problems
13.9
Implement Stack Using Queues
13.9.1
Problem Metadata
13.9.2
Description
13.9.3
Examples
13.9.4
Constraints
13.9.5
Solution - Single Queue Rotation
14
Dynamic Programming and Backtracking
14.0.1
Dynamic Programming
14.0.2
Backtracking Algorithms
14.1
Longest Palindromic Substring
14.1.1
Problem Metadata
14.1.2
Description
14.1.3
Examples
14.1.4
Constraints
14.1.5
Solution - DP via Reversed String
14.2
Letter Combinations of a Phone Number
14.2.1
Problem Metadata
14.2.2
Description
14.2.3
Examples
14.2.4
Constraints
14.2.5
Solution - Backtracking
14.3
Combination Sum
14.3.1
Problem Metadata
14.3.2
Description
14.3.3
Examples
14.3.4
Constraints
14.3.5
Solution - Dynamic Programming (Unbounded Knapsack)
14.4
Permutations
14.4.1
Problem Metadata
14.4.2
Description
14.4.3
Examples
14.4.4
Constraints
14.4.5
Solution - Backtracking with Choose-Explore-Unchoose Pattern
14.4.6
Solution - Backtracking with Visited Array
14.5
Permutations II
14.5.1
Problem Metadata
14.5.2
Description
14.5.3
Examples
14.5.4
Constraints
14.5.5
Solution - Backtracking with Choose-Explore-Unchoose Pattern
14.5.6
Solution - Backtracking with Visited Array
14.6
Unique Paths
14.6.1
Problem Metadata
14.6.2
Description
14.6.3
Examples
14.6.4
Constraints
14.6.5
Solution - DP Grid
14.7
Minimum Path Sum
14.7.1
Problem Metadata
14.7.2
Description
14.7.3
Examples
14.7.4
Constraints
14.7.5
Solution - DP Table
14.8
Climbing Stairs
14.8.1
Problem Metadata
14.8.2
Description
14.8.3
Examples
14.8.4
Constraints
14.8.5
Solution - DP Tabulation
14.8.6
Solution - DP Memoization
14.9
Subsets
14.9.1
Problem Metadata
14.9.2
Description
14.9.3
Examples
14.9.4
Constraints
14.9.5
Solution - Backtracking
14.10
Word Search
14.10.1
Problem Metadata
14.10.2
Description
14.10.3
Examples
14.10.4
Constraints
14.10.5
Solution - DFS Backtracking
14.11
Subsets II
14.11.1
Problem Metadata
14.11.2
Description
14.11.3
Examples
14.11.4
Constraints
14.11.5
Solution - Backtracking with Skip Logic
14.12
Decode Ways
14.12.1
Problem Metadata
14.12.2
Description
14.12.3
Examples
14.12.4
Constraints
14.12.5
Solution - Bottom-Up Dynamic Programming (Tabulation)
14.12.6
Solution 2 - Top-Down Dynamic Programming (Memoization)
14.13
Pascal’s Triangle
14.13.1
Problem Metadata
14.13.2
Description
14.13.3
Examples
14.13.4
Constraints
14.13.5
Solution - Dynamic Programming (Tabulation)
14.14
Word Break
14.14.1
Problem Metadata
14.14.2
Description
14.14.3
Examples
14.14.4
Constraints
14.14.5
Solution 1 - Recursive Prefix Search (Top-Down DP with Memoization)
14.14.6
Solution 2 - Bottom-Up Dynamic Programming
14.14.7
Solution 3 - Trie-Assisted DP
14.15
House Robber
14.15.1
Problem Metadata
14.15.2
Description
14.15.3
Examples
14.15.4
Constraints
14.15.5
Solution - Linear DP
14.16
Maximal Square
14.16.1
Problem Metadata
14.16.2
Description
14.16.3
Examples
14.16.4
Constraints
14.16.5
Solution - Dynamic Programming
14.17
Paint House
14.17.1
Problem Metadata
14.17.2
Description
14.17.3
Examples
14.17.4
Constraints
14.17.5
Solution - Rolling DP
14.18
Longest Increasing Subsequence
14.18.1
Problem Metadata
14.18.2
Description
14.18.3
Examples
14.18.4
Constraints
14.18.5
Solution - Binary Search (Patience Sorting)
14.18.6
Solution - Dynamic Programming
14.19
Best Time to Buy and Sell Stock with Cooldown
14.19.1
Problem Metadata
14.19.2
Description
14.19.3
Examples
14.19.4
Constraints
14.19.5
Solution - State Machine DP
14.20
Coin Change
14.20.1
Problem Metadata
14.20.2
Description
14.20.3
Examples
14.20.4
Constraints
14.20.5
Solution - Dynamic Programming (Unbounded Knapsack)
14.21
Coin Change II
14.21.1
Problem Metadata
14.21.2
Description
14.21.3
Examples
14.21.4
Constraints
14.21.5
Solution - Dynamic Programming (Unbounded Knapsack)
14.22
Palindromic Substrings
14.22.1
Problem Metadata
14.22.2
Description
14.22.3
Examples
14.22.4
Constraints
14.22.5
Solution 1 - Expand Around Center
14.22.6
Solution 2 - Dynamic Programming (Tabulation)
14.23
Minimum Swaps to Make Sequences Increasing
14.23.1
Problem Metadata
14.23.2
Description
14.23.3
Examples
14.23.4
Constraints
14.23.5
Solution - DP with Keep/Swap States
14.24
Count Square Submatrices with All Ones
14.24.1
Problem Metadata
14.24.2
Description
14.24.3
Examples
14.24.4
Constraints
14.24.5
Solution - Dynamic Programming (In-Place)
14.25
Custom Fibonacci Sequence
14.25.1
Metadata
14.25.2
Description
14.25.3
Examples
14.25.4
Constraints
14.25.5
Walkthrough
14.25.6
Analysis
14.25.7
Implementation Steps
14.25.8
Java Code
14.26
Find Index Combinations with Target Weight Sum
14.26.1
Problem Metadata
14.26.2
Description
14.26.3
Examples
14.26.4
Input Format
14.26.5
Output Format
14.26.6
Constraints
14.26.7
Solution - Backtracking with Unbounded Knapsack
14.27
Generate Valid Angle Bracket Sequences
14.27.1
Problem Metadata
14.27.2
Description
14.27.3
Examples
14.27.4
Constraints
14.27.5
Solution - Backtracking
14.28
Minimum Plans to Reach Target Bandwidth
14.28.1
Problem Metadata
14.28.2
Description
14.28.3
Examples
14.28.4
Input Format
14.28.5
Output Format
14.28.6
Constraints
14.28.7
Solution - Dynamic Programming (Unbounded Knapsack)
14.29
Fibonacci Sequence
14.29.1
Problem Metadata
14.29.2
Description
14.29.3
Examples
14.29.4
Constraints
14.29.5
Solution 1 - Top-Down Recursion (Naïve)
14.29.6
Solution 2 - Tail Recursion
14.29.7
Solution 3 - Bottom-Up DP
14.29.8
Solution 4 - Memoized Recursion
14.30
Longest Common Substring
14.30.1
Problem Metadata
14.30.2
Description
14.30.3
Examples
14.30.4
Constraints
14.30.5
Solution - 2D DP Table
14.31
Minimum Operations to One
14.31.1
Problem Metadata
14.31.2
Description
14.31.3
Examples
14.31.4
Constraints
14.31.5
Solution - Memoized Recursion
14.32
Retrieve Optimal Computation
14.32.1
Problem Metadata
14.32.2
Description
14.32.3
Examples
14.32.4
Constraints
14.32.5
Solution - Memoized Recursion
15
Problem Index
15.1
Quick Lookup by Problem ID
15.1.1
LeetCode
15.1.2
HackerRank
15.1.3
Firecode
15.1.4
Other
15.1.5
Interview
15.2
Lookup by Difficulty
15.2.1
Easy Problems
15.2.2
Medium Problems
15.2.3
Hard Problems
15.2.4
Unclassified Problems
15.3
Lookup by Chapter
15.4
Lookup by Technique
15.4.1
Dynamic Programming
15.4.2
Backtracking
15.4.3
Two Pointer
15.4.4
Sliding Window
15.4.5
Greedy
15.4.6
Data Structures
15.4.7
Searching
15.4.8
Matrix Traversal
15.4.9
Tree Traversal
15.4.10
Graph Traversal
15.4.11
Sorting
15.4.12
Statistical Sampling
15.4.13
Game Theory & Optimization
15.5
Lookup by Study Plan
15.5.1
Blind 75
15.5.2
NeetCode 150
15.5.3
Grind 75
15.6
Lookup by Company
15.7
How to Update This Index
15.7.1
Example CSV Entry
15.7.2
Tags Format
15.7.3
Techniques Format
15.8
Summary Statistics
References
Published with bookdown
Technical Interview
Chapter 15
Problem Index
This index helps you find problems by LeetCode ID, difficulty, chapter, or platform.