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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 1141–1170 of 3276 results

  • Tests modeling geometric proximity as a graph problem, using Disjoint Set Union or graph traversal to identify connected components while ensuring exact integer arithmetic and handling duplicate coordinates.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Practice counting binary-grid components when diagonal neighbors connect, changing the usual four-direction island definition.

    GoogleFrontend EngineerCoding & AlgorithmsOnsite
  • Tests graph traversal, bitmask dynamic programming or backtracking with pruning, and prefix counting on small labeled graphs.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an algorithm to compute cell-by-cell coverage counts for an n x n grid given multiple inclusive rectangular regions.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Count the paths across an n by m grid from the bottom-left to the bottom-right cell when each move goes up-right, right or down-right, optionally passing through checkpoints in a required order, modulo a large prime. It tests column-by-column dynamic programming and reducing memory use.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Count super-streak segments in a time-ordered event stream with an O(n) scan. The solution explains maximal segment boundaries, inclusive gap handling, duration and count checks, edge cases, streaming behavior, and changing-threshold follow-ups.

    GoogleData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to parse and process large-scale event logs, perform sessionization based on time gaps, handle out-of-order records and memory constraints, and reason about time and space complexity and optimization strategies in the Coding & Algorithms domain.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Decide string transform with directional tokens and walls evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to handle nested structures using recursion or a stack-based approach to expand string patterns based on repetition factors.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Tests directed graph modeling, cycle detection, and Kahn's algorithm using a min-heap to produce a lexicographically smallest topological sort.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's ability to design and implement a game engine, manage board state and turn logic, validate moves, and apply efficient data structures and algorithms for win detection within the Coding & Algorithms domain.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design an in-memory message logger that records timestamped messages and queries the top-K most frequent messages within any given time range.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to design an efficient data structure for time-series aggregation using a sliding window approach with O(1) time complexity per operation.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design a memory-efficient data structure for sparse or repetitive vector data and implement an arithmetic operation without fully decompressing the representation.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of scalable resource-allocation and matching systems, encompassing data-structure and index design, availability tracking, fragmentation minimization, concurrency control, and failure handling for large node pools.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skill in designing a composite data structure that supports average O(1) insertion, deletion, and uniform random access, and tests understanding of hashing, indexing, randomness, and concurrency control.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design a dynamic data structure that maintains elements while efficiently querying the k-th largest value, necessitating a balance between insertion speed and retrieval performance.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Determine which players in a competition have a uniquely determined ranking given a set of pairwise match outcomes.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of hierarchical relationship modeling, transitive inference across relations, and dynamic data-structure design for tracking manager and peer links.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the ability to implement a depth-first search (DFS) with backtracking to find a specific sequence within a grid, while managing state to avoid reusing the same path.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Determine validity after digit-constrained deletions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to determine connectivity between two nodes in a directed graph, specifically modeling ancestry relationships.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to model a combinatorial game using the Sprague-Grundy theorem and memoization to determine the winner of a state-dependent stack-merging process.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to implement Kahn's algorithm for topological sorting while using a min-priority queue to satisfy specific tie-breaking requirements.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Determine the earliest timestamp at which all nodes in a network become part of a single connected component using a chronological sequence of edge additions.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • A Google coding problem asking you to evaluate a small Lisp-like expression language with integer literals, variables, and add, mult and let forms. It tests tokenizing and parsing nested expressions, lexical scoping in which inner bindings shadow outer ones, and sequential rebinding inside a let.

    GoogleSoftware EngineerCoding & AlgorithmsOther
  • Implement a template engine that recursively resolves variable placeholders using a key-value dictionary while handling circular dependencies, missing keys, and escaped characters.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design an algorithm to rate-limit and deduplicate a stream of robot status messages so identical messages only display if strictly more than ten seconds have elapsed since their last displayed occurrence.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Find the minimum security clearance needed to travel between two nodes in a graph where edges exceeding a given latency threshold cannot be used.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests your ability to process and merge multiple sets of time intervals to find mutually available time windows within a given working day.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite

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