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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 421–450 of 3276 results

  • This problem tests your ability to efficiently find the k-smallest pair sums from two sorted arrays using a heap-based approach to avoid exhaustive search.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an algorithm to find the k pairs of elements with the smallest absolute difference in a strictly increasing sorted array.

    AppleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates algorithmic and data-structure skills, focusing on frequency counting, heap-based selection, streaming updates, and time/space complexity analysis within the Coding & Algorithms domain.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of recursion, algorithmic problem decomposition, and analysis of time complexity when generating constrained move sequences.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency with data structures and algorithms for service inventory operations, including deterministic filtering, attribute matching, graph traversal for transitive dependency resolution, and status propagation across service graphs.

    AppleMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of information retrieval and text representation concepts—specifically TF–IDF weighting, tokenization, term frequency and document frequency—and measures competency in implementing an efficient scoring and ranking algorithm.

    AppleMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the ability to adapt data structure behaviors by implementing a First-In-First-Out (FIFO) queue using only Last-In-First-Out (LIFO) stacks.

    AppleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your understanding of JavaScript closures, asynchronous timers, and the ability to maintain internal state across multiple function invocations.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to implement a binary tree iterator that performs inorder traversal using O(h) extra space, where h is the height of the tree, while maintaining an amortized time complexity of O(1) per call.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of socket programming, stream message framing, internal buffer management, EOF and error handling, input size limits, unit testing, and time/space complexity analysis.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates knowledge and implementation skills in text processing, vector-space models, and information retrieval, covering tokenization, term-frequency and TF–IDF weighting, cosine similarity, and ranking for similarity search within the Coding & Algorithms domain.

    AppleMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates mastery of deep object cloning, reference and memory management, and knowledge of language runtime details such as prototypes, property descriptors, symbol-keyed and non-enumerable properties, and built-in types like Maps, Sets, Dates, RegExps, and typed arrays.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to implement graph traversal algorithms (BFS and DFS) on a 2D grid, focusing on boundary conditions and state management.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Category: Coding & Algorithms — this problem evaluates frequency counting, dictionary-based aggregation, string handling, manual maximum-finding without built-in functions, and stable tie-breaking by first appearance in the input.

    AppleAnalytics EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in Python fundamentals and object-oriented inheritance, focusing on frequency aggregation using a precomputed dictionary, iteration over mappings, and correct handling of ties and empty inputs.

    AppleData EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic implementation and computational thinking across combinatorics, image processing, and vector similarity—specifically testing permutation generation, 2D convolution with explicit boundary handling, and nearest-neighbor retrieval for image embeddings.

    AppleMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of array/matrix manipulation, cache and data structure design, streaming algorithms for median maintenance, and graph theory for cycle detection, with emphasis on algorithmic complexity analysis and handling of edge cases.

    AppleSoftware EngineerCoding & AlgorithmsOnsite
  • Maximize funds with capital-gated projects 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.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Compare both suffix-to-prefix concatenation orders, merge the longest edge overlap, and favor the original string order when overlap lengths tie.

    AppleSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to manipulate array-based data using sorting and linear scanning to identify and merge overlapping intervals.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests graph modeling and shortest-path optimization on a 2D grid with zero-weight transitions and unit-weight bridges using 0-1 BFS or Dijkstra's algorithm.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to optimize matrix multiplication by leveraging data sparsity to avoid unnecessary computations and handle memory efficiently.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's proficiency in object-oriented design, configuration injection, extensibility, state tracking (including ties), and testability when refactoring a Rock–Paper–Scissors tournament to support configurable rounds.

    AppleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in array algorithms, algorithmic efficiency (linear time and constant-space reasoning), and handling edge cases related to non-decreasing order, within the Coding & Algorithms domain.

    AppleData ScientistCoding & AlgorithmsOnsite
  • This question evaluates proficiency in in-place matrix and array manipulation, spatial data transformation, and reasoning about time and space complexity.

    AppleMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • A coding question that asks you to implement a fixed-capacity key-value cache with least-recently-used eviction and run it over a stream of get and put operations. It tests precise recency and eviction rules, updates to keys already in the cache, and the design of a data structure with constant-time operations.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Given a number of tasks and dependency pairs, return the lexicographically smallest order that completes every task while respecting all dependencies, or an empty list when a cycle makes that impossible. Tests topological sorting, cycle detection and deterministic tie-breaking on large dependency graphs.

    AppleSoftware EngineerCoding & AlgorithmsOnsite
  • This set evaluates algorithmic problem-solving and data-structure competence, including mastery of hash tables, linked lists, stacks, queues, heaps, graphs, sliding-window and two-pointer techniques, complexity analysis, and in-place transformations.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This collection evaluates algorithmic problem-solving skills, mastery of fundamental data structures (arrays, strings, hash maps, stacks, queues, trees, graphs, linked lists) and the ability to reason about time and space complexity.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of digit-based state convergence and cycle detection alongside graph traversal and constrained shortest-path search, testing skills in number manipulation, state-space search, and BFS-style exploration.

    AppleSoftware EngineerCoding & AlgorithmsTechnical Screen

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