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Coding & Algorithms interview questions

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

Questions3276

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 2791–2820 of 3276 results

  • Process a stream of wallet events where purchases spend expiring vouchers in priority order before charging a card with zone-based fees, and refunds split between card and new store credit. Tests careful rule-by-rule simulation and integer money math.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a KYC CSV record validator that parses customer records, normalizes fields, and validates tax IDs and owner name matches.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an end-to-end transaction validation pipeline that parses raw CSV records, evaluates behavioral fraud detection rules, and outputs a formatted fixed-width audit report.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a multi-tier KYC verification function that validates business identity inputs against format requirements and an official registry using token-based normalization.

    StripeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Combine recurring 'open' maintenance windows and 'blackout' periods, declared in different local time zones, into the next usable UTC slots after a notice period; tests interval merging, subtraction and week wrap-around.

    StripeSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's competency in modular software design and extensibility, algorithmic filtering and ranking, date arithmetic for birthday proximity, geospatial distance computation, and integration with notification services.

    StubHubSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a flexible, object-oriented recommendation engine that allows for composable filtering and ranking logic using the strategy or decorator pattern.

    StubHubSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a flexible, object-oriented recommendation pipeline using the Strategy and Composite patterns to handle multiple scoring rules and fallback logic.

    StubHubSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to process log data and perform string manipulation by identifying users who visited a specific URL across multiple days and determining the longest common substring between two modified strings.

    SumologicSoftware EngineerCoding & AlgorithmsOnsite
  • These questions evaluate algorithmic problem-solving skills: the first focuses on greedy scheduling and time-step simulation to maximize actions before deadlines while the second tests event aggregation, sorting and grouping logic for sessionization.

    SupioSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to design efficient algorithms for duplicate detection, occurrence counting, and preserving first-occurrence order while reasoning about time and space complexity across in-memory, in-place, and streaming data scenarios.

    TCSData ScientistCoding & AlgorithmsTechnical Screen
  • This problem tests the implementation of the Levenshtein distance algorithm (Edit Distance) and the ability to manage tie-breaking logic when comparing multiple strings against a query.

    TargetBackend EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests the ability to solve interval overlap challenges using the sweep-line algorithm, specifically handling boundary conditions where a loan ends at the exact time another begins.

    TekionSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests dynamic programming optimization by finding the maximum profit from stock trading with a constraint on the total number of allowed transactions.

    TekionSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to manage concurrent asynchronous tasks, specifically implementing logic to return the first 'True' result while efficiently cancelling remaining pending tasks.

    TemporalSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests the ability to write a SQL query to identify consecutive daily login streaks from raw event logs, requiring date deduplication, window functions, and streak length aggregation.

    TemuData EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to map and manipulate encoded card ranks, reason about consecutive sequences with Ace-as-low or Ace-as-high semantics, and identify a missing element within a constrained set.

    TemuSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of sequence analysis and array-processing competencies, including mapping elements between arrays, index lookup, and designing efficient order-dependent algorithms for the "next greater element" problem.

    TemuSoftware EngineerCoding & AlgorithmsOnsite
  • Traverse an m x n matrix clockwise from the outside in, then handle a follow-up where some cells are blockers that the walk must turn away from. Tests careful simulation of direction changes, tracking of visited cells, and a precise rule for when the traversal stops.

    TemuSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates array manipulation, algorithmic optimization, and complexity analysis, specifically the ability to reason about time and space trade-offs and design a linear-time, constant-space approach for computing trapped water.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to compute geometric suffix sums over batched 2D trajectories, testing skills in array manipulation, Euclidean distance computation, and runtime-conscious algorithm design within the Coding & Algorithms domain.

    TeslaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency with tree algorithms, distance computation, and propagation modeling, testing the ability to reason about how a process spreads across parent-child relationships in a tree.

    TeslaBackend EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage concurrent resources using synchronization primitives, ensuring workers can safely alternate between two exclusive tasks while maintaining thread safety.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to solve a counting problem using dynamic programming by identifying overlapping subproblems in a sequence of numeric mappings.

    TeslaSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's competency in designing and implementing efficient data structures for interval management, contiguous memory allocation, fragmentation handling, tag-based resource tracking, and algorithmic complexity analysis.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates array manipulation, pairwise comparison, and algorithmic efficiency by requiring identification of minimal absolute differences and construction of ordered latency pairs.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A linked list whose nodes may each carry one side branch, with branches nested like a binary tree, must be flattened into a single doubly linked list with every branch spliced between its parent and the parent's original successor. It tests pointer rewiring, ordering rules for nested branches, and handling very deep nesting.

    TeslaSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to process strings and manage state (character frequency) to determine exact matches versus partial matches, commonly used in word-guessing games.

    TeslaSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding of 2D convolution mechanics and practical low-level tensor manipulation, including kernel shape handling, padding and stride effects, multi-channel input/output interactions, and optional bias integration.

    TeslaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design a data structure that supports basic key-value operations with an added transactional rollback mechanism using a stack-based approach.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen

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