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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 571–600 of 3276 results

  • This problem tests grid traversal via dynamic programming or recursion, combined with the sliding window technique to identify unique character patterns within string segments.

    BloombergSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve Magic Dictionary and unknown traversal states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of graph and grid traversal concepts, specifically identifying connected components in a binary matrix and familiarity with traversal strategies such as BFS and DFS.

    BloombergSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to perform a vertical-order traversal of a binary tree by mapping nodes to relative column indices and sorting them by their depth and value.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manipulate overlapping intervals and perform specific tree traversals to extract structural information.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to handle nested data structures through recursive parsing, maintain efficient state using hash maps and dynamic arrays, and implement sliding window techniques to manage constraints in a stream.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates design and analysis skills for string-matching data structures that support one-edit queries and for binary tree traversal with coordinate-based ordering, testing understanding of data structures, search algorithms, sorting, and complexity analysis within the Coding & Algorithms domain.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to handle three distinct algorithmic scenarios: greedy logic for circular traversal, stack-based syntax validation, and state-space exploration on a 2D grid.

    BloombergSoftware EngineerCoding & AlgorithmsOnsite
  • This two-part question evaluates combinatorial enumeration and subset-generation concepts for arrays alongside string parsing and parentheses-sequence validation for noisy input, measuring algorithm design, correctness, and complexity reasoning in array and string contexts.

    BloombergSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to use a stack data structure to maintain LIFO ordering for matching paired symbols within a string.

    BloombergSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Form the maximum number of valid trains from a shared pool of locomotives and railcars, breaking ties by maximizing total railcar length.

    BnsfSoftware EngineerCoding & AlgorithmsOnsite
  • Determine the minimum number of cars to remove from a queue so that no single retained car nor any adjacent retained pair exceeds a bridge's weight limit.

    BnsfSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates skills in frontend data handling and UI behavior, including implementing sortable lists, maintaining user-selected sort field and direction across refreshes, constructing nested comment trees from flat parentId references, and filtering content while preserving descendant visibility.

    BobyardSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manage character frequency counts and sliding window techniques to identify properties of unique substrings and characters.

    BoeingSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skill in matching records across unsorted collections, focusing on data structures, aggregation and handling one-to-one and one-to-many relationships between bookings and payments.

    Booking.comSoftware EngineerCoding & AlgorithmsOnsite
  • This 90-minute assessment evaluates algorithmic problem-solving skills including string manipulation and grouping for anagram detection, digit-level reasoning for one-swap maximization, and text tokenization with aggregation and ranking for sentiment-based scoring.

    Booking.comSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Analyze Python Functions: Improve Readability and Efficiency states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Boston Consulting GroupData ScientistCoding & AlgorithmsTechnical Screen
  • Compute Top-K word frequencies under a path 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.

    BoxSoftware EngineerCoding & AlgorithmsOnsite
  • Design out-of-order windowed stream processor 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.

    BoxSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of bitwise operations and low-level integer manipulation, along with the ability to reason about the time and space complexity of bit-level operations.

    BoxSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of rate-limiting algorithms, time-based state management, and concurrent programming concepts, including synchronization and test design for boundary and timing behaviors.

    BoxSoftware EngineerCoding & AlgorithmsOnsite
  • Implement a leaky-bucket rate limiter evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    BoxSoftware 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 Solve classic troubleshooting & algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    BoxSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's debugging and root-cause analysis skills, familiarity with unit testing and regression prevention, and ability to modify a small codebase to fix defects within the coding and algorithms domain.

    BrexSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates implementation-level skills in resource accounting and state management, specifically handling gem-cost mappings, per-color discounts, bounded arithmetic, and transactional updates to player state.

    BrexSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's competence in data structures, graph traversal and flood-fill concepts, complexity analysis, and scalable system design for sparse board representations.

    BridgeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in string/path normalization, manipulation of hierarchical data structures, stack-based iterator design, lazy versus eager flattening strategies, and algorithmic time/space complexity analysis in the Coding & Algorithms domain.

    BridgeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests string manipulation, handling of sign logic, and carrying operations for large integer arithmetic without utilizing large integer libraries.

    ByteDanceSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Practice an interval-scheduling problem where meetings may be delayed and room-number tie rules affect the final count. The prompt tests precise simulation, large-input complexity, integer safety, and careful handling of simultaneous room availability.

    ByteDanceSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests tree traversal, hash map utilization for parent-child relationship tracking, and identification of the root node in a graph-based structure.

    ByteDanceSoftware EngineerCoding & AlgorithmsTechnical Screen

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