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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 3271–3276 of 3276 results

  • This problem tests greedy strategy and sorting to determine the maximum possible count of distinct values in an array after applying exactly one offset from a given set of allowed integers to each element.

    xAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of scheduling constraints, frequency analysis, and time-complexity reasoning required to minimize total execution time under per-type cooldown restrictions.

    xAISoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of string-to-digit encoding, prefix-based retrieval, and efficient preprocessing for fast query-time lookup in large dictionaries.

    xAISoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of concurrent programming, parallel algorithm design, sorting algorithms, and merging techniques under multi-threaded execution, focusing on thread-safety, deterministic correctness despite scheduling variability, and performance trade-offs.

    xAISoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of transactional state management, nested transactions, visibility semantics for set/delete operations, and efficient in-memory data-structure manipulation.

    xAISoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of cache design and LRU eviction semantics with weighted resource accounting, plus data-structure and amortized-complexity reasoning needed to support O(1) average-time operations.

    xAISoftware EngineerCoding & AlgorithmsOnsite

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