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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 91–120 of 3276 results

  • This problem tests SQL data aggregation skills with NULL handling and algorithmic proficiency in dynamic programming to count palindromic subsequences in a string.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of breadth-first traversal, URL normalization, domain scoping, duplicate detection, and retry/error handling, measuring algorithmic design and robustness in networked code.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design an in-memory inverted index for text retrieval, requiring efficient tokenization, case-insensitive mapping, and dynamic updates to a collection of sentences.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a cache with O(1) time complexity for both get and put operations by combining a hash map with a doubly linked list.

    AmazonSoftware EngineerCoding & AlgorithmsHR Screen
  • This problem tests your ability to use a greedy approach combined with a frequency map to construct the lexicographically largest sequence under specific constraints.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question tests string manipulation, modular arithmetic, and the ability to optimize performance by trading space for time using a precomputed lookup table.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates programming fluency in numerical data processing and algorithmic implementation for computing moving averages and handling edge cases in time-series sequences, and it applies to Data Scientist roles while falling under the Coding & Algorithms category.

    AmazonData ScientistCoding & AlgorithmsOnsite
  • This question evaluates a candidate's ability to reason about circular arrays, distance computations, and query-efficient algorithms, assessing concepts such as modular indexing and cumulative distances.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests string manipulation and two-pointer traversal techniques to verify if a string is a palindrome while ignoring non-alphanumeric characters and case.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of graph algorithms, reachability, and algorithmic complexity by determining whether adding a directed edge would introduce a cycle in an otherwise acyclic directed graph.

    AmazonApplied ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of tree traversal and sequence matching in N-ary trees, including handling non-unique node values and maintaining traversal state across branches.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's ability to work with circular array structures and prefix sums to compute shortest distances on a ring topology. It tests practical coding skill in efficiently handling wraparound arithmetic and cumulative sums, a common pattern in algorithm interviews assessing array manipulation and optimization under scale constraints.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Tests dynamic programming and string manipulation by calculating the minimum number of single-character edits (insertions, deletions, substitutions) needed to transform one string into another.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates parsing and processing of timestamped event logs to compute message latencies and implementation of constrained grid path search, testing competencies in file I/O, record alignment/matching, time-delta computation, graph traversal, and stateful backtracking.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithm design and data-structure skills—frequency counting, hashing, and handling edge cases such as ties and a no-mode rule—within the coding and algorithms domain for data scientist roles.

    AmazonData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic efficiency in array processing, specifically reasoning about nearest-smaller relationships and the use of auxiliary structures to achieve subquadratic performance.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates a candidate's understanding of graph traversal concepts, grid-based state propagation, and reachability analysis in time-evolving systems.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of greedy and resource-allocation strategies along with combinatorial reasoning to maximize operations under discrete constraints.

    AmazonSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This two-part question evaluates array manipulation and optimization skills—specifically range-update minimization to enforce a nondecreasing sequence and greedy pairing/matching to maximize summed primary resources—testing algorithm design, complexity reasoning, and constraint handling.

    AmazonSoftware 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 Compute optimal locker placement with obstacles states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's competency in temporal interval reasoning, event-stream processing, and handling incomplete or unsorted logs to determine peak concurrent occupancy.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates array-manipulation and algorithmic problem-solving skills, focusing on computing a product-for-each-index using prefix and postfix accumulation concepts while reasoning about edge cases such as zeros, negative numbers, and integer overflow.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This prompt evaluates integer reachability and invariant reasoning via repeated additive transformations (testing number-theoretic reachability and state-space analysis) alongside resource-aware scheduling and grouping logic for minimizing completion time under type and memory constraints, and it falls under the Coding & Algorithms domain.

    AmazonSoftware 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 Compute shortest path with obstacles states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to maintain dynamic statistics in a data stream using efficient data structures to achieve logarithmic insertion and constant-time retrieval.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage overlapping time intervals efficiently, requiring an understanding of sorting or priority queues to track resource utilization.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to use greedy strategies combined with efficient data structures to manage resource allocation and optimize revenue based on priority-based demand.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of binary tree algorithms, recursion versus iterative traversal strategies, and competence in algorithmic analysis including time and space complexity and handling deep-recursion stack overflow when computing a tree's diameter.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to traverse an undirected graph using graph search algorithms to identify and count disjoint subgraphs.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests data manipulation, hash set/map aggregation, and date deduplication to identify users with repeat visits across distinct calendar days.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen

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