Top 145 Algorithms Interview Questions
Practice the most frequently asked algorithms interview questions. Each question includes expert tips, sample answers, and AI-powered practice.
Shortest Word Distance
Spotify asks this to evaluate your ability to optimize space complexity while maintaining linear time performance. They value engineers who can solve problems efficiently without unnecessary memory overhead, reflecting their need for scalable audio streaming infrastructure where resource management is critical.
Find the Difference
Stripe values engineers who write efficient, bug-free code that handles edge cases gracefully. This question evaluates your ability to optimize space complexity beyond brute force while demonstrating logical precision. Interviewers specifically look for candidates who recognize mathematical properties like XOR to solve problems in O(n) time with O(1) space, reflecting a deep understanding of algorithmic fundamentals rather than just syntax.
Symmetric Tree
Microsoft asks this question to evaluate a candidate's ability to visualize recursive structures and handle edge cases in tree traversals. It tests whether you can translate the abstract concept of symmetry into a concrete algorithmic comparison between left and right subtrees without relying on complex data structures, demonstrating clean logic and attention to null pointer handling.
Find Closest Element in BST
Netflix asks this to evaluate a candidate's ability to leverage specific data structure properties rather than brute-forcing solutions. They want to see if you recognize that BST traversal allows for O(h) time complexity by pruning branches, demonstrating logical efficiency and the capacity to optimize algorithms under real-world streaming constraints.
Closest Binary Search Tree Value
Spotify asks this to evaluate your ability to leverage BST properties for O(log n) efficiency rather than brute force. They specifically test if you can optimize space complexity by replacing recursion with an iterative approach, demonstrating mastery of tree traversal and stack management under constraints.
Longest Palindrome
Amazon asks this to evaluate your ability to optimize space complexity while handling edge cases like mixed-case characters. They specifically test if you can recognize that palindrome construction relies on character frequency parity rather than substring continuity, assessing your analytical thinking and efficiency mindset.
Pascals Triangle
Apple interviewers use Pascal's Triangle to assess a candidate's ability to recognize recursive patterns and translate mathematical definitions into efficient iterative code. They specifically evaluate attention to edge cases, such as handling numRows equal to zero or one, and the capacity to optimize space complexity by reusing existing rows rather than allocating new memory structures unnecessarily.
Climbing Stairs (Dynamic Programming)
Uber interviewers use this problem to assess a candidate's ability to recognize overlapping subproblems and optimal substructure, the core pillars of dynamic programming. They specifically evaluate whether you can transition from an inefficient brute-force recursive solution to an optimized iterative approach with O(n) time and O(1) space complexity, demonstrating practical algorithmic efficiency skills required for high-scale ride-matching systems.
Meeting Rooms
Spotify asks this question to evaluate a candidate's ability to optimize data structures for resource management, mirroring their need for efficient scheduling systems. It tests fundamental algorithmic thinking, specifically the application of sorting to solve interval overlap problems, while assessing clarity in communicating logic under pressure.
Two Sum
Google asks the Two Sum problem to evaluate a candidate's ability to optimize time complexity beyond brute force. Interviewers specifically look for proficiency in using hash maps to trade space for speed, demonstrating logical thinking and the capacity to identify edge cases like duplicate elements or negative numbers efficiently.
Maximum Subarray (Kadane's Algorithm)
Adobe asks this question to evaluate a candidate's ability to optimize brute-force solutions into linear time complexity, reflecting their focus on performance-critical creative software. It tests algorithmic thinking, specifically the capacity to recognize overlapping subproblems and apply dynamic programming principles like Kadane's Algorithm efficiently.
Range Sum Query - Immutable
Microsoft interviewers use this problem to evaluate a candidate's ability to optimize time complexity through preprocessing. They specifically test if you recognize that repeated range queries on static data warrant an O(1) lookup strategy rather than recalculating sums, demonstrating foundational algorithmic thinking and memory-time trade-off awareness.
Reverse Vowels of a String
Stripe values engineers who write clean, efficient code that handles edge cases gracefully. This question tests your ability to manipulate strings in-place using the Two-Pointer technique, a core skill for optimizing memory usage. It evaluates whether you can identify patterns, handle case sensitivity correctly, and implement an O(n) solution without allocating extra space.
The Power of Two
Interviewers at Uber ask this to evaluate a candidate's ability to optimize for performance and memory efficiency. They specifically test knowledge of binary representation, as Bit Manipulation is critical in high-throughput systems like ride-matching algorithms where O(1) operations reduce latency significantly.
Valid Parentheses
Apple interviewers ask this to evaluate a candidate's ability to model real-world hierarchical structures using fundamental data structures. They specifically test if you can recognize patterns requiring Last-In-First-Out (LIFO) logic, such as nested scopes or matching pairs. The question assesses your grasp of stack operations, edge case handling like empty strings or mismatched brackets, and your capacity to write clean, efficient code under pressure without relying on complex libraries.
Find the Town Judge
Airbnb asks this problem to evaluate a candidate's ability to model real-world trust relationships using graph theory concepts without explicitly drawing the graph. They specifically look for candidates who can optimize space complexity from O(N^2) adjacency matrices to O(N) counters, demonstrating efficiency and clarity in handling edge cases like isolated nodes or multiple potential judges.
Boyer-Moore Majority Vote Algorithm
Google asks this to evaluate a candidate's ability to optimize for strict memory constraints while maintaining linear time complexity. It tests logical reasoning, pattern recognition in data streams, and the capacity to discard unnecessary storage by leveraging mathematical properties of majority elements rather than relying on hash maps or sorting.
Binary Tree Level Order Traversal
Netflix evaluates this question to assess a candidate's ability to implement Breadth-First Search efficiently, as their streaming infrastructure relies heavily on hierarchical data processing. They specifically test if you can manage state within a queue to traverse levels without mixing node depths, ensuring your code handles edge cases like empty trees while maintaining optimal O(n) time complexity.
Is Subsequence
Cisco evaluates this question to assess a candidate's ability to implement efficient two-pointer logic without unnecessary overhead. It tests fundamental algorithmic thinking, specifically the capacity to solve problems with O(n) time complexity and O(1) space constraints. The interviewer looks for clarity in handling edge cases like empty strings and the ability to translate logical conditions into clean, bug-free code quickly.
Search in a Binary Search Tree
Netflix values engineers who can write efficient, readable code that scales. This question tests your understanding of BST properties to avoid unnecessary traversal, demonstrating logical reasoning and algorithmic efficiency. They want to see if you recognize the O(log n) optimization over a naive O(n) search, reflecting their culture of high performance and minimal resource waste.
Min Cost Climbing Stairs
Spotify asks this to evaluate your ability to identify overlapping subproblems and apply dynamic programming efficiently. They want to see if you can recognize that the optimal path to any stair depends only on the previous two states, allowing you to optimize space complexity from O(n) to O(1). This tests your core algorithmic thinking and code optimization skills under pressure.
Balanced Binary Tree
Spotify asks this to assess your ability to think recursively and optimize for time complexity beyond basic traversal. They want to see if you recognize that a naive solution checking height at every node leads to O(N^2) inefficiency, whereas an optimal approach computes height and balance status in a single pass.
Best Time to Buy and Sell Stock (I)
Amazon interviewers use this problem to assess your ability to optimize for time complexity while maintaining code clarity. They specifically evaluate whether you can identify that a single pass solution is superior to nested loops, reflecting their 'Bias for Action' and focus on efficient resource usage in high-scale systems.
Edit Distance
LinkedIn asks this to evaluate a candidate's mastery of dynamic programming and their ability to decompose complex string manipulation problems into overlapping subproblems. It tests logical rigor in defining state transitions while assessing whether you can optimize space complexity, a critical skill for LinkedIn's high-scale data processing environments.
Split Array Largest Sum
Microsoft asks this to evaluate a candidate's ability to transform an optimization problem into a decision problem, a key skill for distributed systems. It tests if you recognize that minimizing the maximum sum is monotonic, allowing binary search on the answer rather than brute force. This reveals your capacity to handle resource allocation constraints and optimize load balancing scenarios efficiently.
Alien Dictionary
Microsoft asks the Alien Dictionary problem to evaluate a candidate's ability to model real-world constraints as graph problems. They specifically test topological sorting skills, edge case handling like cycles and invalid orders, and logical reasoning under pressure. This assesses whether you can translate abstract rules into an efficient algorithmic solution.
Find Median from Data Stream
IBM evaluates candidates on their ability to optimize real-time data processing, a core competency for their cloud and cognitive systems. This specific problem tests your mastery of heap data structures, understanding of time complexity trade-offs between insertion and retrieval, and capacity to design balanced algorithms for streaming data scenarios common in enterprise environments.
Russian Doll Envelopes
Microsoft asks this problem to evaluate a candidate's ability to decompose complex geometric constraints into standard algorithmic patterns. They specifically test if you can recognize that sorting by width transforms the problem into finding the Longest Increasing Subsequence on heights, while handling edge cases like equal dimensions correctly. This assesses optimization skills and deep understanding of time complexity trade-offs.
Reverse Nodes in k-Group
Microsoft uses this problem to evaluate a candidate's mastery of pointer manipulation and edge-case handling in linked lists. It tests the ability to decompose complex state changes into modular steps while maintaining O(1) space complexity. Interviewers specifically look for how you manage group boundaries and handle incomplete final groups without crashing or creating memory leaks.
Remove Duplicate Letters
Salesforce evaluates this question to assess a candidate's mastery of greedy algorithms and stack-based data structures. It specifically tests the ability to optimize for lexicographical order while maintaining element uniqueness, requiring candidates to balance immediate character selection with future availability constraints.
Decode Ways II
Amazon interviewers ask this to evaluate your mastery of dynamic programming under constraints. Specifically, they test if you can handle ambiguity with the wildcard '*' while managing modular arithmetic to prevent integer overflow. This mirrors Amazon's Leadership Principle of 'Dive Deep,' requiring candidates to analyze edge cases like leading zeros and multi-digit combinations rigorously before coding.
Reverse Pairs
LinkedIn asks this to evaluate a candidate's mastery of divide-and-conquer strategies beyond standard sorting. They specifically test the ability to modify established algorithms like Merge Sort to handle complex constraints, such as the factor of two in reverse pairs. This assesses whether you can optimize time complexity from O(n^2) to O(n log n) while maintaining logical rigor under pressure.
Serialize and Deserialize Binary Tree
Google asks this to evaluate your mastery of tree traversal algorithms and your ability to handle edge cases in data persistence. It tests if you can design a lossless encoding scheme that preserves structural information, not just values. Interviewers look for your capacity to choose between breadth-first and depth-first approaches while managing memory constraints and ensuring the serialization logic is robust against null pointers.
Median of Two Sorted Arrays
Microsoft asks this question to evaluate a candidate's ability to optimize beyond brute force solutions and their mastery of binary search on non-standard data structures. It tests deep algorithmic thinking, specifically the capacity to handle edge cases like empty arrays or uneven partitioning while maintaining strict logarithmic time complexity constraints.
Shortest Distance from All Buildings
Salesforce asks this to evaluate a candidate's ability to handle complex graph traversal problems with multiple constraints. They specifically test if you can optimize for space and time when performing Breadth-First Search from multiple sources, ensuring the solution scales efficiently without redundant calculations or memory overflows.
Word Search II
Stripe values engineers who can balance algorithmic rigor with practical system performance. This question tests your ability to optimize brute-force search using a Trie for prefix pruning, demonstrating deep understanding of space-time trade-offs. It evaluates whether you can handle complex backtracking without hitting Time Limit Exceeded errors, a critical skill for high-throughput payment systems.
Trapping Rain Water
Meta asks this problem to evaluate a candidate's ability to optimize space complexity while maintaining linear time performance. It tests logical reasoning, pattern recognition in array traversal, and the capacity to move beyond naive brute-force solutions. The interviewer specifically looks for how you handle edge cases and whether you can derive the two-pointer optimization independently without relying on pre-memorized patterns.
N-Queens
Stripe asks this to evaluate a candidate's mastery of recursive backtracking and constraint satisfaction under pressure. They specifically look for the ability to visualize board state changes, manage complex indexing without off-by-one errors, and optimize pruning strategies to avoid unnecessary computation on large N values.
Wildcard Matching
Adobe asks this to evaluate a candidate's mastery of dynamic programming and recursive thinking under pressure. The problem tests the ability to handle state transitions with multiple wildcard rules, specifically managing the non-deterministic nature of the asterisk character. It reveals whether you can optimize naive recursion into an efficient solution while maintaining code clarity.
Longest Increasing Path in a Matrix
Uber interviewers use this problem to assess a candidate's ability to combine graph traversal with dynamic programming optimization. They specifically evaluate whether you can identify overlapping subproblems in a grid-based DFS and implement memoization to prevent exponential time complexity, reflecting Uber's need for scalable algorithmic solutions in logistics.
Minimum Window Substring
Stripe engineers value robustness and efficiency in handling high-volume transactional data streams. This problem tests your mastery of the sliding window technique, a critical pattern for processing real-time data without redundant computations. Interviewers specifically look for your ability to manage character frequency maps dynamically and optimize time complexity from brute force O(n*m) to linear O(n), ensuring solutions scale under Stripe's strict latency requirements.
Word Ladder
Salesforce asks this Hard-level graph problem to evaluate a candidate's mastery of Breadth-First Search (BFS) for shortest path discovery. It specifically tests the ability to model implicit graphs where nodes are words and edges represent single-character transformations. Interviewers assess whether you can optimize space complexity using bidirectional search or efficient neighbor generation, reflecting Salesforce's focus on scalable, high-performance data processing solutions.
Expression Add Operators
Stripe asks this problem to evaluate a candidate's mastery of backtracking algorithms and their ability to handle complex state management. It specifically tests how well you manage edge cases like leading zeros, operator precedence, and integer overflow while maintaining clean, readable code under pressure.
Smallest Range Covering Elements from K Lists
Spotify engineers ask this to evaluate your ability to manage dynamic state across multiple data streams efficiently. It tests if you can move beyond brute-force solutions to optimize time complexity using a Min-Heap. They specifically look for your understanding of how to balance range minimization with the constraint of covering every list simultaneously.
Max Points on a Line
Google asks this problem to evaluate a candidate's ability to handle geometric edge cases and numerical precision issues. They specifically test whether you can move beyond brute-force solutions to optimize time complexity while managing floating-point inaccuracies inherent in slope calculations. It reveals your depth of understanding regarding hash maps, mathematical representations of lines, and robust error handling.
Maximum Profit in Job Scheduling
Google asks this to evaluate a candidate's ability to combine dynamic programming with binary search for optimization. It tests whether you can recognize overlapping subproblems, sort data effectively, and optimize an O(n^2) solution to O(n log n). This specific combination reveals how well you handle resource-constrained scheduling scenarios common in Google's infrastructure.
Shortest Palindrome
Meta evaluates candidates on this problem to assess mastery of string manipulation algorithms and the ability to optimize beyond naive brute-force solutions. Interviewers specifically look for your capacity to apply advanced preprocessing techniques like KMP to solve complex pattern-matching problems efficiently, demonstrating strong analytical thinking under time pressure.
Dijkstra's Algorithm
Oracle evaluates this to assess mastery of graph theory and priority queue optimization. They specifically look for your ability to handle edge cases like disconnected components or zero-weight edges while maintaining O(E log V) efficiency. This tests logical rigor under pressure, a core competency for building scalable enterprise infrastructure.
Sliding Window Maximum
Google engineers ask this to evaluate your ability to optimize time complexity beyond naive solutions. They specifically test if you can leverage a Deque to maintain state efficiently, demonstrating mastery of data structures and sliding window patterns essential for high-throughput systems.
Maximal Rectangle
Oracle evaluates candidates on their ability to decompose complex spatial problems into manageable sub-problems. This question specifically tests mastery of dynamic programming, stack-based optimization, and the capacity to recognize pattern reduction from a 2D grid problem to a 1D histogram challenge under strict time constraints.
Reconstruct Itinerary
Stripe evaluates candidates on graph traversal and state management under constraints. This question tests the ability to model real-world flight data as a directed graph, handle complex backtracking logic when dead-ends occur, and implement Hierholzer's algorithm efficiently. It specifically assesses lexical ordering requirements and the candidate's proficiency with DFS in non-trivial scenarios.
Count of Smaller Numbers After Self
Tesla evaluates this question to assess a candidate's ability to optimize brute-force solutions for real-time systems. They specifically look for mastery of divide-and-conquer strategies or advanced data structures like Fenwick Trees, which are critical for handling high-volume sensor data processing efficiently within their autonomous driving stacks.
Merge k Sorted Lists
Amazon asks this question to evaluate a candidate's mastery of advanced data structures and ability to optimize for scalability. Specifically, they test your capacity to move beyond naive solutions that degrade performance as input size grows. The interviewer looks for proficiency in using Min-Heaps to manage complexity efficiently, demonstrating the 'Invent and Simplify' leadership principle by finding elegant algorithmic shortcuts rather than brute-force methods.
Wiggle Sort II
Microsoft asks Wiggle Sort II to evaluate a candidate's ability to handle complex in-place array manipulations under strict constraints. This problem specifically tests mastery of partitioning algorithms, understanding of index mapping logic, and the capacity to optimize for O(n) time and O(1) space simultaneously. It reveals whether an engineer can balance theoretical correctness with practical memory efficiency.
Sudoku Solver
Apple evaluates candidates on rigorous problem-solving and algorithmic depth. This question tests your mastery of backtracking, a core technique for constraint satisfaction problems. Interviewers assess your ability to design recursive solutions that explore possibilities while pruning invalid paths efficiently. They specifically look for clean code structure, handling of edge cases like empty grids, and the logical flow required to solve complex puzzles without external libraries.
Largest Rectangle in Histogram
Uber asks this problem to evaluate a candidate's ability to optimize brute-force solutions for real-time logistics systems. They specifically test proficiency with Monotonic Stacks, a critical pattern for finding next/smaller elements efficiently. This assesses whether you can handle O(N) constraints required for high-volume data processing in ride-sharing algorithms.
Design Searchable Dictionary (Trie + DFS)
Netflix evaluates candidates on scalable data structure design and recursive problem-solving. This specific question tests your ability to implement a Trie for efficient prefix storage while handling complex wildcard logic via Depth-First Search. It assesses whether you can balance time complexity against memory usage, a critical skill for their high-throughput streaming recommendation engines.
The Skyline Problem
Stripe evaluates candidates on their ability to handle complex geometric problems with edge cases. This question tests mastery of sweep-line algorithms and priority queues, requiring precise handling of overlapping intervals and simultaneous events. It specifically assesses logical rigor in managing state transitions when building heights change at identical x-coordinates.
LRU Cache Implementation
Uber asks this to evaluate a candidate's ability to balance memory constraints with performance requirements in high-throughput systems. They specifically test mastery of pointer manipulation, data structure composition, and the rigorous application of O(1) complexity constraints. This problem reveals whether you can architect solutions that handle real-time ride-matching latency without degrading system stability under heavy load.
Shortest Path Visiting All Nodes
Airbnb asks this to assess a candidate's ability to handle combinatorial explosion in real-world routing scenarios, such as optimizing delivery or maintenance routes. They specifically evaluate mastery of state-space search using BFS combined with bitmasking to track visited nodes efficiently. This tests if you can balance time complexity against memory constraints while solving a variation of the NP-hard Traveling Salesperson Problem.
Search in Rotated Sorted Array
Salesforce asks this to evaluate a candidate's ability to adapt binary search logic to non-standard data structures. It tests whether you can handle edge cases, maintain O(log n) efficiency under constraints, and demonstrate rigorous logical reasoning when standard assumptions about sorted arrays no longer apply.
Merge Intervals
Google asks 'Merge Intervals' to evaluate a candidate's ability to handle sorting logic and edge cases in real-world scheduling or resource allocation problems. Interviewers specifically look for how you approach data normalization, your grasp of time complexity trade-offs, and whether you can systematically reduce overlapping states without missing boundary conditions.
Remove Nth Node From End of List
Oracle interviewers use this problem to assess a candidate's ability to optimize space complexity while manipulating linked structures. They specifically evaluate whether you can implement the two-pointer technique efficiently without allocating extra memory for arrays or stacks, demonstrating strong algorithmic thinking and mastery of pointer arithmetic in constrained environments.
Reconstruct Queue (Alternative Sort)
Meta asks this problem to evaluate a candidate's ability to handle complex sorting logic and greedy algorithm design. It tests whether you can recognize that standard sorting fails here, requiring a custom comparator strategy. Interviewers specifically look for your capacity to transform a seemingly chaotic reconstruction task into an ordered process by prioritizing height and count constraints efficiently.
Game of Life
Apple evaluates candidates on their ability to optimize space complexity while maintaining code clarity. This problem specifically tests your understanding of bitwise operations, in-place matrix manipulation, and edge case handling without allocating extra memory. It reveals how you balance algorithmic efficiency with practical constraints typical of Apple's resource-conscious engineering culture.
Maximum Product Subarray
Amazon interviewers ask this question to evaluate a candidate's ability to handle state management with negative numbers, which often breaks standard maximum subarray logic. It tests dynamic programming optimization skills and the capacity to maintain multiple states (max and min) simultaneously. The problem specifically probes whether you can identify edge cases like zeros and negative flips that cause simple greedy approaches to fail, ensuring you write robust code under pressure.
Palindrome Partitioning
Meta asks Palindrome Partitioning to evaluate a candidate's mastery of recursion and backtracking algorithms. Interviewers specifically test the ability to explore all possible solution paths while pruning invalid branches efficiently. This problem assesses logical decomposition skills, understanding of string manipulation, and the capacity to manage state during complex recursive calls without external libraries.
Longest Palindromic Substring
Meta evaluates candidates on their ability to optimize brute-force solutions into efficient algorithms. This question specifically tests your understanding of string manipulation, edge case handling like odd versus even length palindromes, and your capacity to implement the 'Expand Around Center' technique with O(n^2) time complexity while maintaining clean, readable code.
Find K Pairs with Smallest Sums
Apple interviewers ask this to evaluate a candidate's ability to optimize brute-force solutions using advanced data structures. They specifically test if you can recognize that sorting all pairs is inefficient and instead leverage the sorted nature of input arrays with a Min-Heap for optimal performance. This assesses your grasp of time complexity trade-offs and priority queue manipulation in real-world constraint scenarios.
Evaluate Division (Union-Find)
Google interviewers use this problem to assess a candidate's ability to model real-world relationships as graph structures and select the optimal algorithmic approach. They specifically evaluate your understanding of Disjoint Set Union (Union-Find) with path compression and rank optimization, testing if you can handle dynamic connectivity problems efficiently rather than just solving isolated equations.
Add Two Numbers
Cisco evaluates candidates on their ability to manipulate low-level data structures efficiently. This question tests logical precision in handling edge cases like carry propagation and unequal list lengths. It specifically assesses whether you can implement a linear time solution while maintaining code clarity, a critical skill for network infrastructure development where performance is paramount.
Partition Equal Subset Sum
Stripe evaluates this question to assess a candidate's ability to transform a real-world partitioning challenge into a dynamic programming solution. They specifically look for the skill of recognizing NP-complete problems and optimizing them using memoization or space reduction, reflecting their need for engineers who write efficient, scalable code for high-volume financial transactions.
House Robber II
Microsoft asks House Robber II to evaluate a candidate's ability to decompose circular dependency problems into solvable linear subproblems. Interviewers specifically test if you recognize that the circular constraint forces a choice between two scenarios: excluding the first house or excluding the last. This assesses your pattern recognition skills and your capacity to adapt standard dynamic programming solutions to modified constraints without overcomplicating the logic.
Product of Array Except Self
Amazon interviewers use this problem to evaluate a candidate's ability to optimize space complexity while adhering to strict constraints. They specifically test if you can recognize that division is forbidden, forcing you to think about prefix and suffix products. This assesses your proficiency in handling edge cases like zeros and your capacity to design an O(n) solution without auxiliary arrays for the final result.
Minimum Path Sum
Salesforce asks this to evaluate a candidate's ability to optimize recursive solutions into efficient dynamic programming algorithms. They specifically test if you can recognize overlapping subproblems and the optimal substructure property within grid-based pathfinding scenarios, ensuring you can balance time complexity against space constraints in real-world data processing tasks.
Container With Most Water
Apple interviewers ask this problem to evaluate a candidate's ability to optimize brute-force solutions using the Two-Pointer technique. They specifically test logical deduction skills: understanding why moving the shorter line is the only viable strategy to maximize area. This assesses algorithmic efficiency and the capacity to reason about constraints without relying on memorized patterns.
Minimum Height Trees
Salesforce interviewers ask this to evaluate your ability to optimize graph traversal beyond standard BFS. They specifically test if you recognize that the center of a tree minimizes height, rather than brute-forcing every node. This assesses your skill in identifying edge cases, understanding topological sorting properties, and writing efficient O(N) solutions under pressure.
Count Primes
Amazon asks this question to evaluate a candidate's ability to optimize for time complexity when handling large datasets, a core requirement for their high-scale systems. Interviewers specifically look for the transition from naive O(n^2) brute force approaches to the efficient O(n log log n) Sieve of Eratosthenes algorithm. They assess whether you understand memory trade-offs and can implement clean, bug-free code under pressure.
Populating Next Right Pointers in Each Node
Meta interviewers use this problem to evaluate a candidate's ability to optimize space complexity beyond standard recursion. They specifically test if you can distinguish between perfect binary trees and general trees, requiring distinct traversal strategies. The question assesses your mastery of pointer manipulation, level-order processing without extra queues, and your capacity to adapt algorithms when constraints change.
Min Stack
Meta evaluates this question to assess a candidate's ability to optimize space-time trade-offs in constrained environments. They specifically look for understanding of how auxiliary data structures can maintain state without degrading performance, testing your grasp of amortized analysis and stack manipulation logic rather than just brute-force iteration.
Inorder Successor in BST
Netflix values engineers who write efficient, self-contained code without relying on external libraries. This question tests your ability to leverage BST properties rather than performing a full traversal. It evaluates logical deduction, edge case handling for nodes with or without right subtrees, and your capacity to optimize space complexity from O(N) to O(1).
Graph Valid Tree
Interviewers at LinkedIn ask this to assess your ability to model real-world connectivity problems, such as social network dependencies. They evaluate whether you can distinguish between a tree and a general graph by identifying cycles or disconnected components. This tests your grasp of fundamental data structures like Union-Find or traversal algorithms under constraints.
Count Complete Tree Nodes
Microsoft evaluates candidates' ability to leverage specific data structure properties for optimization rather than defaulting to brute force. This question tests if you recognize that a complete binary tree's structural constraints allow for logarithmic time complexity, demonstrating deep algorithmic insight and the capacity to solve problems efficiently under resource constraints.
Maximum Length of Repeated Subarray
Microsoft evaluates this question to assess a candidate's ability to recognize overlapping subproblems, a core trait for optimizing recursive solutions. It tests whether you can transition from naive brute-force approaches to efficient Dynamic Programming, demonstrating logical structuring and memory management skills essential for building scalable backend systems.
Battleships in a Board
Uber interviewers use this problem to assess a candidate's ability to optimize for space complexity while maintaining algorithmic clarity. They specifically evaluate if you can identify that battleships are contiguous components and count only their unique starting points, rather than using BFS or DFS which would require O(m*n) extra space. This tests your understanding of greedy strategies and single-pass iteration constraints.
Is Graph Bipartite?
Salesforce asks this to evaluate a candidate's ability to model real-world constraints, such as scheduling or matching problems, using graph theory. They specifically test logical reasoning, proficiency in traversal algorithms like BFS or DFS, and the capacity to handle edge cases like disconnected components without crashing the system.
Serialize and Deserialize BST
Amazon interviewers ask this to evaluate your ability to leverage domain-specific constraints, specifically the BST property, rather than treating trees as generic structures. They assess your algorithmic efficiency mindset by checking if you recognize that preorder traversal alone is sufficient for reconstruction without storing null markers. This tests optimization skills and your capacity to reduce space complexity while maintaining O(n) time performance.
Fraction to Recurring Decimal
Salesforce interviewers ask this to evaluate your ability to handle edge cases and manage state in deterministic algorithms. They specifically test if you can detect cycles in long division using hash maps, ensuring you don't rely on floating-point arithmetic which introduces precision errors. This problem assesses logical rigor and attention to detail, critical for building reliable enterprise financial or data processing systems.
Implement Trie (Prefix Tree)
Google asks this to evaluate a candidate's mastery of pointer manipulation and memory management. It tests the ability to design nested data structures that optimize prefix lookups, a core requirement for autocomplete systems. Interviewers specifically assess how you handle edge cases like null pointers, empty strings, and partial word matches while maintaining O(m) time complexity.
Queue Reconstruction by Height
Stripe interviewers ask this problem to evaluate a candidate's ability to optimize sorting strategies and apply greedy logic under constraints. They specifically test whether you can recognize that processing elements in a specific order (tallest first) simplifies the insertion logic, transforming a complex O(N^2) simulation into an efficient solution. This assesses your capacity to reframe algorithmic problems by changing the perspective of data traversal.
Top K Frequent Elements
Uber interviewers ask this to evaluate your ability to optimize for performance-critical systems like real-time ride matching or surge pricing. They specifically test if you can move beyond naive sorting solutions to achieve better than O(n log n) complexity using advanced data structures like heaps or bucket sort, demonstrating deep algorithmic efficiency.
Unique Binary Search Trees II
Meta evaluates this question to assess a candidate's mastery of recursive backtracking and dynamic programming optimization. They specifically look for the ability to handle state explosion in combinatorial problems while maintaining clean, readable code. The problem tests if you can decompose a complex structural generation task into smaller subproblems involving root selection and left/right subtree construction.
Decode Ways
Stripe asks 'Decode Ways' to evaluate a candidate's mastery of dynamic programming and their ability to handle edge cases involving zero handling and invalid sequences. This problem tests whether you can recognize overlapping subproblems and construct an optimal solution without redundant calculations, reflecting Stripe's need for engineers who write efficient, bug-free code under pressure.
Rotate Image
Airbnb asks this to evaluate a candidate's mastery of in-place matrix manipulation and spatial reasoning. They specifically look for the ability to optimize space complexity to O(1) while maintaining code clarity. This problem tests if you can visualize geometric transformations without relying on extra data structures, a critical skill for performance-sensitive engineering roles.
Minimum Genetic Mutation
Google asks this question to evaluate a candidate's ability to model real-world biological processes as graph traversal problems. They specifically test proficiency in Breadth-First Search for finding shortest paths in unweighted graphs, attention to detail regarding edge constraints like single-character mutations, and the capacity to translate abstract logic into efficient code under pressure.
Permutations
Cisco evaluates this question to assess a candidate's mastery of backtracking algorithms and recursive thinking, which are critical for network pathfinding and state management. They specifically look for the ability to handle combinatorial complexity without missing edge cases or creating duplicate results, reflecting their need for engineers who can design robust, error-free protocols.
Number of Islands
Amazon asks this problem to evaluate a candidate's ability to traverse graph structures efficiently using standard algorithms like DFS or BFS. It tests core competency in handling 2D grids, managing visited states to prevent cycles, and optimizing for time complexity O(m*n). Interviewers specifically look for clean code implementation and the ability to discuss trade-offs between recursion depth and iterative approaches under pressure.
Design HashMap
Google asks this to evaluate a candidate's deep understanding of data structures, specifically hash table mechanics and collision resolution strategies. They assess whether you can translate theoretical concepts into efficient code without relying on built-in libraries, testing your ability to handle edge cases like resizing, load factors, and bucket management under pressure.
Maximal Square
Adobe asks this problem to evaluate a candidate's ability to recognize overlapping subproblems and apply dynamic programming for optimization. They specifically test if you can transform a brute-force geometric check into an efficient O(mn) solution, demonstrating strong algorithmic thinking and spatial reasoning skills essential for their graphics and software engineering roles.
Longest Increasing Subsequence (LIS)
Netflix evaluates this question to assess a candidate's ability to optimize solutions beyond brute force, mirroring their culture of high performance and scalability. They specifically look for the transition from a basic dynamic programming approach to an optimized O(n log n) solution using binary search or patience sorting, demonstrating deep algorithmic insight and efficiency awareness.
Flatten Binary Tree to Linked List
Google interviewers use this problem to assess a candidate's mastery of pointer manipulation and recursive thinking within constrained memory environments. They specifically evaluate the ability to traverse complex data structures while maintaining in-place modification constraints, which mirrors real-world scenarios where optimizing space complexity is critical for performance.
K Closest Points to Origin
Netflix values engineers who balance algorithmic efficiency with practical system constraints. This question tests your ability to optimize space complexity by using a Max-Heap instead of sorting the entire array, ensuring you understand how to maintain a dynamic subset of data efficiently without unnecessary overhead.
Unique Paths II
Airbnb asks this variation of the classic grid problem to assess a candidate's ability to adapt standard dynamic programming patterns to real-world constraints. They specifically evaluate how you handle edge cases, such as obstacles blocking the start or end points, and whether you can optimize space complexity while maintaining code clarity for scalable travel platform logic.
Spiral Matrix
Uber engineers frequently ask the Spiral Matrix problem to assess a candidate's ability to manage complex boundary conditions and state transitions without external libraries. It specifically evaluates spatial reasoning, precision in loop logic, and the capacity to maintain code clarity while handling edge cases like single-row or single-column matrices.
Find the Celebrity
Uber interviewers use this problem to assess your ability to optimize brute-force solutions and think critically about constraints. They specifically evaluate if you can identify the underlying graph structure, recognize that a celebrity must have an in-degree of n-1 and out-degree of 0, and apply a two-pointer or elimination strategy to achieve O(n) time complexity instead of the naive O(n^2).
Generate Parentheses
Google asks this question to evaluate a candidate's mastery of recursion, backtracking, and state management. It tests the ability to prune invalid search spaces efficiently rather than generating all permutations blindly. Interviewers specifically look for logical clarity in maintaining balance constraints while constructing valid sequences dynamically.
Insert Interval
Stripe values engineers who can handle complex state transitions and data integrity. This question tests your ability to manage edge cases in interval logic, such as merging overlapping ranges or handling non-overlapping insertions without creating duplicates. It evaluates your precision in algorithmic thinking and your capacity to write clean, bug-free code under pressure.
Decode String
Apple interviewers use the 'Decode String' problem to evaluate a candidate's ability to manage nested structures and state transitions. They specifically test proficiency with stack-based algorithms, which are fundamental for parsing complex data formats like JSON or code compilers. The question reveals how well you handle recursion logic iteratively and your capacity to debug edge cases involving multiple levels of nesting without relying on built-in parser functions.
Delete Operation for Two Strings
Microsoft asks this problem to evaluate a candidate's ability to transform a complex deletion task into a classic dynamic programming subproblem. They specifically look for the insight that minimizing deletions is mathematically equivalent to maximizing the Longest Common Subsequence (LCS). This tests your pattern recognition skills and your capacity to reduce an O(N*M) brute force scenario into an optimized solution.
Shortest Path in Binary Matrix
Amazon asks this question to evaluate a candidate's mastery of Breadth-First Search (BFS) for unweighted shortest path problems. They specifically look for the ability to handle edge cases like blocked start/end points and to implement queue-based traversal efficiently without recursion depth issues, reflecting their emphasis on operational excellence and clean, scalable code.
Validate Binary Search Tree (BST)
Apple interviewers ask this to evaluate your ability to handle recursive constraints beyond simple local comparisons. They specifically test if you understand that a node's validity depends on the entire history of its ancestors, not just immediate children. This assesses your rigor in edge case handling and your capacity to implement stateful logic within recursion, ensuring robust tree validation under strict engineering standards.
Find All Duplicates in an Array
Meta interviewers ask this to evaluate your mastery of in-place array manipulation and index-based hashing. They specifically test if you can optimize space complexity to O(1) while maintaining linear time, a common requirement for high-scale systems where memory is constrained. This problem reveals whether you understand how to repurpose existing data structures creatively rather than relying on standard library helpers.
Group Anagrams
Airbnb asks this to evaluate your ability to optimize data grouping logic efficiently. They specifically test if you can recognize that sorting strings is a reliable canonical key for anagrams, rather than relying on less efficient character counting or brute-force comparisons. This assesses your grasp of hash map trade-offs and string manipulation complexity.
Daily Temperatures
Airbnb asks this to evaluate your mastery of stack-based optimizations for time-sensitive problems. They specifically test if you can identify the O(n^2) brute-force trap and pivot to a Monotonic Stack solution, demonstrating your ability to optimize algorithms for real-world scalability where data volume is high.
Unique Paths
Netflix evaluates this problem to assess a candidate's ability to optimize solutions beyond brute force. They specifically look for the transition from an O(m*n) dynamic programming approach to an O(min(m,n)) combinatorial solution, testing mathematical insight and efficiency awareness crucial for their high-performance engineering culture.
Find the Longest Word in Dictionary through Deleting
Interviewers at Uber ask this to evaluate your ability to implement efficient subsequence checking algorithms while handling complex tie-breaking logic. They specifically test if you can optimize for time complexity using a two-pointer approach rather than brute force, and whether you can correctly prioritize lexicographical order when multiple solutions exist.
Longest Substring Without Repeating Characters
Amazon asks this question to evaluate a candidate's mastery of the Sliding Window technique, a core competency for optimizing O(N^2) solutions to O(N). Interviewers specifically look for your ability to manage state efficiently using hash maps or arrays while handling edge cases like duplicate characters. It tests logical precision and code clarity under pressure, aligning with Amazon's Leadership Principle of 'Dive Deep' into algorithmic efficiency.
Permutation in String
IBM interviewers ask this to evaluate a candidate's ability to optimize space complexity beyond brute force. They specifically test if you can recognize that checking all permutations is inefficient and instead apply the sliding window technique with frequency maps. This demonstrates mastery of string manipulation, hash map operations, and algorithmic efficiency under constraints.
Perfect Squares
Airbnb asks this to evaluate a candidate's ability to model real-world optimization problems, such as minimizing transaction costs or resource allocation. They assess proficiency in dynamic programming and breadth-first search, specifically testing if you can identify overlapping subproblems and make optimal local choices that lead to a global minimum efficiently.
Word Search
Uber interviewers ask the Word Search problem to evaluate a candidate's mastery of backtracking and depth-first search (DFS) algorithms. They specifically look for your ability to handle state management, such as tracking visited cells to prevent reusing characters in a single path. This question tests whether you can systematically explore a complex search space while managing recursion stack overflow risks and optimizing time complexity in grid-based traversal scenarios.
Subsets
Tesla evaluates candidates on their ability to handle combinatorial logic and optimize for both time and space efficiency. This question tests your mastery of recursion, backtracking mechanics, and iterative state management. It reveals whether you can systematically explore all possibilities without duplication or infinite loops, a critical skill for embedded systems and autonomous decision-making algorithms where exhaustive search paths must be pruned effectively.
Longest Consecutive Sequence
Tesla evaluates candidates on algorithmic efficiency and the ability to handle large-scale data processing within strict constraints. This question specifically tests if you can distinguish between sorting (O(n log n)) and hashing (O(n)), proving you understand time complexity trade-offs essential for real-time vehicle systems where performance is critical.
The 3n + 1 Problem (Collatz Conjecture)
Netflix values engineers who balance raw algorithmic thinking with practical performance optimization. This problem tests your ability to handle non-trivial iteration logic, manage state efficiently through memoization, and optimize for edge cases like input order without relying on brute-force methods that would fail under scale.
Minimum Time Difference
Airbnb asks this question to evaluate a candidate's ability to handle circular data structures and edge cases involving time wrapping. It tests logical precision in calculating differences across midnight, as well as the skill to optimize for O(N log N) or O(1) space solutions rather than naive comparisons.
Longest Common Subsequence (LCS)
Airbnb asks the Longest Common Subsequence problem to evaluate a candidate's ability to recognize overlapping subproblems and apply dynamic programming efficiently. They are testing whether you can transition from brute-force recursion to an optimized DP solution, demonstrating logical structuring skills essential for building scalable infrastructure that handles complex data matching tasks.
Meeting Rooms II
Microsoft interviewers use this problem to evaluate a candidate's ability to optimize resource allocation under constraints. They specifically test proficiency in time complexity analysis, particularly the trade-offs between sorting and heap operations. The question assesses whether you can recognize overlapping intervals efficiently and design an algorithm that scales well for large datasets common in cloud infrastructure systems.
Counting Bits
Amazon asks this question to evaluate a candidate's ability to optimize solutions beyond brute force, specifically testing their grasp of dynamic programming and bit manipulation patterns. They want to see if you can recognize that the number of set bits in an integer relates to smaller subproblems, demonstrating the 'Invent and Simplify' leadership principle by finding efficient algorithms.
Find the Duplicate Number (Floyd's Cycle)
Interviewers at LinkedIn ask this to assess your ability to recognize non-obvious mathematical patterns in data structures. They specifically evaluate whether you can map array indices to a linked list cycle, demonstrating deep algorithmic thinking beyond standard sorting or hashing solutions. This tests your mastery of space-time trade-offs under strict O(1) memory constraints.
Find All Anagrams in a String
Cisco evaluates candidates on their ability to optimize string processing for network packet analysis and pattern matching. This question tests mastery of the sliding window technique, a critical skill for handling real-time data streams efficiently without excessive memory overhead or nested loops that degrade performance.
Search a 2D Matrix
IBM interviewers ask this question to evaluate a candidate's ability to recognize hidden data structures within complex constraints. They specifically test if you can transform a 2D problem into a 1D search space using mathematical mapping rather than brute force. This assesses your optimization mindset, understanding of logarithmic time complexity, and capacity to handle edge cases in sorted arrays.
Number of Connected Components in an Undirected Graph
Apple interviewers ask this to evaluate a candidate's ability to model real-world connectivity problems using fundamental graph algorithms. They specifically test whether you can choose between BFS, DFS, or Union-Find based on constraints like edge density and memory usage. This question reveals your grasp of time complexity trade-offs and your capacity to implement robust traversal logic without getting lost in edge cases.
Sum of Two Integers
Google interviewers ask this to verify your deep understanding of how hardware processes arithmetic at the binary level. They evaluate if you can bypass standard abstractions to solve constraints using bitwise logic, specifically testing your grasp of carry propagation and XOR operations rather than rote memorization of syntax.
Add and Search Word - Data structure design
Google asks this to evaluate your ability to balance time and space complexity when designing data structures. They specifically test if you can implement a Trie (prefix tree) that handles wildcard searches efficiently, rather than using simple linear scans which fail at scale.
Rotate List
Meta evaluates this problem to assess a candidate's ability to manipulate pointer structures efficiently without allocating extra space. They specifically look for optimization skills, as rotating a list naively often leads to O(N*K) complexity. The interviewer wants to see if you recognize the cyclic nature of the operation and can derive an O(N) solution by identifying the new tail node mathematically rather than simulating each rotation step.
Word Break
IBM evaluates this question to assess a candidate's mastery of dynamic programming and recursive thinking. They specifically look for the ability to break complex string segmentation problems into overlapping subproblems, optimize solutions from exponential time complexity to polynomial, and handle edge cases like empty strings or non-existent words without crashing.
Coin Change
Tesla evaluates candidates on this problem to assess optimization skills and logical rigor under constraints. They specifically look for the ability to transition from a naive recursive solution to an efficient Dynamic Programming approach, demonstrating how you handle overlapping subproblems. This mirrors real-world challenges in battery management systems where minimizing resource usage is critical for performance and safety.
Maximum Swap
Amazon interviewers ask this question to evaluate a candidate's ability to optimize brute-force logic into an efficient linear-time solution. They specifically test if you can identify that swapping the rightmost smaller digit with the largest available larger digit yields the optimal result, demonstrating strong analytical thinking and mastery of array traversal techniques.
Number of Boomerangs
Apple interviewers ask this to evaluate your ability to optimize brute-force solutions using hash maps for constant-time lookups. They specifically test if you can recognize geometric patterns, handle edge cases like duplicate points or floating-point precision, and efficiently calculate combinatorial permutations without redundant calculations.
Jump Game
Adobe asks the Jump Game problem to evaluate a candidate's ability to optimize solutions using greedy logic rather than brute force recursion. They specifically test if you can recognize that looking ahead for the furthest reachable point is more efficient than exploring every possible path. This assesses your capacity to handle array manipulation problems with O(n) time complexity, a skill critical for building performant UI rendering engines and animation systems at Adobe.
Find Peak Element
Salesforce asks this to evaluate a candidate's ability to optimize time complexity beyond linear scanning. They specifically test if you can apply binary search logic to non-sorted data by recognizing that local gradients guarantee a peak exists, demonstrating strong algorithmic intuition and problem-solving under constraints.
3Sum
Airbnb asks the 3Sum problem to evaluate a candidate's ability to optimize brute-force solutions using sorting and the two-pointer technique. They specifically look for proficiency in handling edge cases like duplicate triplets and managing time complexity constraints efficiently, which mirrors their need for scalable, high-performance code in real-world booking systems.
Course Schedule (Topological Sort)
Oracle interviewers use this problem to evaluate a candidate's ability to model real-world dependency systems as directed graphs. They specifically assess whether you can identify cycles, which represent impossible scheduling scenarios in academic or enterprise workflows. This tests your grasp of topological sorting, a fundamental concept for managing complex task dependencies efficiently.
Cheapest Flights Within K Stops
Amazon asks this variation of the shortest path problem to evaluate a candidate's ability to modify standard algorithms under constraints. They specifically test your understanding of trade-offs between BFS, Dijkstra, and Bellman-Ford when a hop limit exists. The interviewer wants to see if you can handle state-space expansion where the 'visited' set must include both node identity and current stop count, reflecting Amazon's focus on solving complex logistical routing problems efficiently.
Search for a Range (First and Last Position)
Spotify evaluates candidates on algorithmic precision and edge-case handling. This question tests if you can optimize a linear scan to logarithmic time using binary search variants. It specifically assesses your ability to maintain sorted array invariants while finding boundary conditions, a skill critical for their large-scale data processing pipelines.
Maximum XOR of Two Numbers in an Array
Google interviewers ask this to evaluate a candidate's mastery of bit manipulation and their ability to optimize brute-force solutions. They specifically test if you can recognize that comparing every pair is inefficient, requiring a shift from O(N^2) to O(32N) using a Trie. This assesses your capacity to think in binary representations and design data structures that exploit bitwise properties for performance.
Ready to practice algorithms questions?
Get AI-powered feedback on your answers with our mock interview simulator.
Start Free Practice