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Coding & Algorithms interview questions

3276 Coding & Algorithms questions from 366 companies, with hints, runnable code and solution walkthroughs.

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273 easy2539 medium464 hard

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Coding & Algorithms interview questions by the numbers

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Katkat has 3,276 Coding & Algorithms interview questions from 366 companies; the most come from Amazon (7%), Meta (7%) and Google (6%). By difficulty: 8% easy, 78% medium and 14% hard. The most common round is Technical Screen (52%). Frequent concepts include Algorithms, Data Structures, Arrays and Greedy.

Companies (366)

Difficulty

  • Easy8% · 273
  • Medium78% · 2539
  • Hard14% · 464

Interview rounds

  • Technical Screen52% · 1706
  • Onsite33% · 1080
  • Online Assessment13% · 427
  • HR Screen1% · 37
  • Other1% · 26

Roles

  • Software Engineer80% · 2629
  • Machine Learning Engineer8% · 253
  • Data Scientist7% · 241
  • Data Engineer1% · 45
  • Backend Engineer1% · 26

Frequent concepts

  • Algorithms9% · 302
  • Data Structures7% · 228
  • Arrays5% · 176
  • Greedy5% · 164
  • Optimization5% · 151
  • Hash Map4% · 124

Showing 31–60 of 3276 results

  • Count distinct integers with frequency exactly one using complete occurrence counts, including empty arrays and separated duplicates.

    AgodaData EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates array manipulation, index-based reasoning, and algorithmic problem-solving skills related to identifying value pairs that meet a numeric target.

    AgodaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests tree reconstruction from a stream of out-of-order parent-child updates, requiring efficient hierarchical state management and cycle detection.

    Ai2Software EngineerCoding & AlgorithmsTechnical Screen
  • Tests sorting and linear scanning techniques to merge overlapping closed intervals, with attention to shared boundaries, nested ranges, and large input scale.

    Aim Intelligent MachineSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a function to allocate an order across inventory batches using FIFO (oldest timestamp first, with batch ID tie-breaker), returning allocation details and any unfilled quantity without mutating the input.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates algorithm design and data-structure selection skills, focusing on greedy allocation, ordering by priority and recency, aggregation of transaction amounts, and analysis of time complexity.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to identify connected components in a 2D grid using graph traversal (BFS/DFS) and aggregate properties associated with those components.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in combinatorial optimization and set-coverage with cost minimization, including handling case-insensitive service matching and enumerating minimal solution combinations.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates the ability to manipulate interval availability data, reason about contiguous date ranges and split boundaries, and design efficient pairing algorithms with attention to time and space complexity.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests greedy algorithm design and stack-based data structure manipulation to satisfy relative ordering constraints within a sequence of digits.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Determine the maximum number of candies you can collect given an initial set of boxes, where each box may be locked or unlocked, contain candies, contain keys to other boxes, and contain other boxes.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Count representations of a positive integer as one or more consecutive positive integers, including the one-term representation. Derive the arithmetic condition for each sequence length and use a square-root bound rather than testing every possible starting value.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's competency in algorithmic problem solving, data structure selection, API design, complexity analysis, and testing through implementation of a Connect Four game engine.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in designing dynamic data structures for mutable rooted trees, including maintenance of subtree sums, parent/child link management, and analysis of update and query complexities within the Coding & Algorithms domain; it emphasizes practical application of algorithmic design coupled with conceptual understanding of invariants and amortized complexity. It is commonly asked in technical interviews because it probes reasoning about correctness and performance under mutations, handling edge cases such as subtree deletion and reattachment, and the ability to specify algorithmic approaches and complexity guarantees rather than implementation details.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to detect if two linked lists merge, specifically when they may contain cycles, by requiring logic to identify loop entry points and intersection nodes.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • Determine if a subset of layover activities can be booked such that their total cost exactly matches a target voucher balance, handling floating-point currency without precision loss.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates combinatorial optimization and algorithm design skills, focusing on capacity-constrained selection (subset-sum/knapsack-style reasoning), deterministic tie-breaking, and complexity analysis within the Coding & Algorithms domain.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates string-processing and algorithmic design skills, including knowledge of efficient lookup data structures, palindrome properties, handling of edge cases, and time/space complexity analysis.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manipulate digits and understand greedy strategies to construct the smallest possible number after applying specific constraints.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • Flatten an arbitrarily deep mixture of integers and lists while preserving left-to-right order. The challenge emphasizes an iterative stack solution that handles empty lists, very deep nesting, and up to 200,000 nodes without mutating the input.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates implementation skills for game state management, move handling, and efficient winner-detection algorithms, testing competence in data structures, algorithmic complexity analysis, and correctness under edge cases.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to design efficient data structures and algorithms for real-time game state management, including win detection, API design, time/space complexity analysis, and handling edge cases such as full or out-of-range columns.

    AirbnbSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Implement URL query parameter extraction and a greedy text line-wrapper that enforces maximum line length and prevents orphan words on the final line.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design and implement a nested-list iterator supporting `hasNext`, `next`, and an in-place `remove` operation that alters the original data structure.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in graph algorithms and optimization, focusing on reasoning about weighted directed acyclic graphs and maximizing a path score that combines node rewards and edge time costs.

    AirbnbSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in weighted interval scheduling, dynamic programming concepts, and the use of efficient data structures for large-scale scheduling problems, including handling duplicate times, large reward values, and memory constraints.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to use tree-based dynamic programming to solve an optimization challenge where you must select a subset of nodes with no two being adjacent, while maximizing the sum of their values.

    AirbnbSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to use dynamic programming to determine if a specific target sum can be achieved using a subset of given item values and how to find the minimum subset size that hits that target.

    AirbnbMachine Learning EngineerCoding & AlgorithmsOnsite
  • Tests dynamic programming for the unbounded knapsack/coin change problem, focusing on finding the minimum number of canisters to reach an exact volume and reconstructing the optimal selection.

    AirbnbMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Design and implement an in-memory timestamped credit ledger that supports deposits, transfers, spending with delayed cashback rewards, account merges, balance queries, and spend rankings.

    AirbnbSoftware EngineerCoding & AlgorithmsOnline Assessment

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