Interval Algorithm Patterns for Coding Interviews
Why Interval Problems Matter in Interviews Interval problems appear in scheduling, calendar, and range queries — and in coding interviews […]
Algorithms, Coding Interview Questions
← Tech Interview
Algorithms
Master fundamental and advanced algorithms essential for technical interviews at top companies. This category covers sorting algorithms, search algorithms, graph algorithms, and optimization techniques that form the foundation of computer science problem-solving.
What You’ll Learn:
Sorting algorithms: Quick sort, merge sort, heap sort
Search techniques: Binary search and variations
Graph algorithms: DFS, BFS, Dijkstra’s, topological sort
Optimization: Dynamic programming, greedy algorithms
Time and space complexity analysis
Difficulty Progression: Start with basic sorting and searching, then progress to graph algorithms and dynamic programming.
Interview Frequency: Extremely high – algorithms appear in 80%+ of technical interviews at Google, Amazon, Facebook, Microsoft, and Apple.
Algorithms, Coding Interview Questions
String Algorithm Patterns for Coding Interviews
Why String Algorithms Matter in Interviews String problems are ubiquitous in technical interviews at Google, Meta, Amazon, and Microsoft. Key
Algorithms, Coding Interview Questions
Graph Algorithm Patterns for Coding Interviews
Why Graph Algorithms Matter in Interviews Graph problems appear constantly in technical interviews because they model real systems: social networks
Algorithms, Coding Interview Questions, Heap
Two Heaps Interview Pattern
The Two Heaps Pattern Two heaps maintain the lower and upper halves of a data stream, allowing O(1) access to
Algorithms, Coding Interview Questions, Data Structures
Matrix Traversal Interview Patterns
Grid Traversal Fundamentals Most matrix problems involve: (1) BFS from one or multiple source cells, (2) DFS to explore connected
Algorithms, Coding Interview Questions, Data Structures
Ordered Map (TreeMap / SortedList) Interview Patterns
When to Use an Ordered Map (Sorted Dict / TreeMap) An ordered map maintains keys in sorted order with O(log
Algorithms, Coding Interview Questions, String
String Hashing Interview Patterns
Why String Hashing? Naive string comparison is O(L) per comparison where L is the string length. String hashing converts a
Algorithms, Coding Interview Questions
Two Pointers Advanced Interview Patterns
When to Use Two Pointers Two pointers reduce O(n²) brute force to O(n) or O(n log n) by exploiting sorted
Algorithms, Coding Interview Questions
Bit Manipulation Interview Patterns
Essential Bit Operations x & y # AND: both bits must be 1 x | y # OR: at least
Algorithms, Coding Interview Questions, Graphs
Topological Sort Interview Patterns
What is Topological Sort? A topological ordering of a directed acyclic graph (DAG) is a linear ordering of vertices such
Algorithms, Coding Interview Questions
Stack Interview Patterns
Core Idea A stack (LIFO) is the right tool when the most recently seen element determines the action for the
Algorithms, Coding Interview Questions
Divide and Conquer Interview Patterns
The Pattern Divide and conquer splits a problem into independent subproblems, solves each recursively, and combines the results. Three steps:
Algorithms, Coding Interview Questions, Math
Number Theory Interview Patterns
GCD and LCM Euclidean algorithm: gcd(a,b) = gcd(b, a%b), base case gcd(a,0) = a. Time O(log min(a,b)). LCM: lcm(a,b) =
Algorithms, Coding Interview Questions
Prefix Sum Interview Patterns
Core Idea Build a prefix array where prefix[i] = arr[0] + arr[1] + … + arr[i-1]. Then any range sum
Algorithms, Coding Interview Questions, Design
Object-Oriented Design Patterns for Coding Interviews
Design patterns appear in coding interviews in two ways: the interviewer asks you to implement a specific pattern, or you’re