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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 841–870 of 3276 results

  • Find a subset of items whose cumulative bitwise OR does not exceed a given limit such that the total profit is maximized.

    Concentric AiSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests the ability to optimize a weighted distance metric by leveraging the independent nature of x and y coordinates in Manhattan geometry.

    Concentric AiSoftware EngineerCoding & AlgorithmsOnline Assessment
  • A coding problem that asks whether a partially filled 9x9 Sudoku board is consistent, meaning no row, column or 3x3 box repeats a digit among its filled cells. It tests careful bookkeeping of row, column and box membership without attempting to solve the puzzle.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to efficiently read the end of a growing file using file pointers and to implement a sliding time-window check for sensor heartbeat events.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates competency in efficient file I/O and streaming techniques for implementing tail, and in graph search and shortest-path algorithms with path reconstruction for computing minimum monster cost in a grid.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • Confluent software-engineer technical-screen coding question: implement tail(path, N) to print the last N lines of a possibly multi-GB file or an unbounded stream without loading it into memory. It tests a backward block scan for seekable files versus an O(N) ring buffer for non-seekable streams, plus correct handling of \n/\r\n/\r newlines, UTF-8 multibyte characters, missing trailing newlines, and extremely long lines, with follow-ups on tail -f, log rotation/truncation, and the -c last-N-bytes option.

    ConfluentSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A coding problem about resolving function calls: given a library of function signatures, some variadic in their last parameter, return every function that accepts each queried list of argument types. It tests precise matching rules, indexing signatures for many queries and deterministic output ordering.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage a collection of values under global update operations while maintaining the ability to efficiently extract the minimum value.

    ConfluentSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates the ability to aggregate pairwise user preferences, implement majority-based comparison rules with deterministic tie-breakers, and compute a global ranking via beat counts.

    ConfluentSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This multi-part prompt evaluates skills in function signature and type matching, resource-constrained file I/O and streaming for large files, and data-structure design for randomized queues including multiset equality, synchronization, and compact run-length encodings.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • Solve constrained monster traversal 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.

    ConfluentSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A coding problem that checks a partially filled 9x9 Sudoku board and completes it when possible. Solutions must detect givens that already break the row, column or box rules, recognize boards with no valid completion, and return a canonical completed grid, testing constraint checking and search.

    ConfluentSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in HTTP client communication with token-based authentication, parsing structured responses into data models, relational database interaction including handling duplicate records, configuration management, and robust error handling and testing.

    CoreweaveSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests the ability to interact with external APIs, handle asynchronous operations with retries, and implement conditional filtering based on system metadata.

    CoreweaveSite Reliability EngineerCoding & AlgorithmsOnsite
  • This question evaluates HTTP and JSON parsing, CSV processing, hierarchical data modeling, sorting, and algorithmic efficiency for building and printing an organizational chart.

    CortexSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of grid-graph traversal and shortest-path concepts, including identification of connected components and reasoning about minimal bridging distance between regions.

    CoupangSoftware EngineerCoding & AlgorithmsOnsite
  • This question tests your ability to traverse a binary search tree efficiently by leveraging its ordering property to find the node value closest to a given target number.

    CoupangSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of voting algorithms, tie-breaking rules, ballot processing, and correctness under edge cases such as incomplete or exhausted ballots, and is commonly asked to assess algorithmic implementation, state simulation, and careful handling of corner cases in interview settings.

    CourseraSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic implementation skills and understanding of voting systems, including aggregation of first-place preferences and the conceptual mechanics of elimination-based ranked-choice counting.

    CourseraBackend EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic thinking and implementation skills related to string construction, time and auxiliary space complexity analysis, and handling boundary/edge-case off-by-one errors.

    Credit GenieSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Simulate wind gusts over a grid in which every cell holds a number of leaves: each gust shifts all leaves one cell in its direction, and leaves pushed off the edge are lost for good. Return how many leaves remain, testing careful two-dimensional state updates and boundary handling under time pressure.

    CrestaSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Given two strings, return the length of the longest suffix of the first string that is also a prefix of the second. The problem tests precise string indexing, the direction of the overlap, and boundary cases such as no overlap at all or an overlap covering the whole shorter string.

    CrestaSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to model a 2D grid as a graph and use graph traversal algorithms like DFS or BFS to count distinct connected components.

    CrowdstrikeSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to combine binary search on the answer with graph traversal techniques (BFS/DFS/Union-Find) to solve optimization problems on a 2D grid.

    CrowdstrikeSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to handle overlapping time intervals and apply conditional overrides to calculate the total charge for a billing period.

    CrusoeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement interval override logic for half-open ranges and calculate the top-k labels based on total active duration with lexicographical tie-breaking.

    CrusoeSoftware EngineerCoding & AlgorithmsOnsite
  • Rebuild a binary search tree with distinct values from its postorder traversal and return the rebuilt tree's preorder traversal. The problem tests BST ordering properties, traversal orders, and meeting a strict O(n) time bound on inputs that include deeply skewed trees.

    CubistSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's understanding of Merkle trees, filesystem-aware hashing, directory traversal, and diff algorithms for detecting file-level changes.

    CursorSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests logic implementation and data structure traversal, requiring the integration of conditional logic (fee waivers) into a sequential processing pipeline.

    DRWData EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests string manipulation, greedy algorithm logic, and the ability to track character frequency counts to identify and prune violations of a constraint.

    DRWData EngineerCoding & AlgorithmsOnline Assessment

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