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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 781–810 of 3276 results

  • This problem tests your ability to perform a two-pass Breadth-First Search (BFS) or Depth-First Search (DFS) on an undirected tree to find the longest path and reconstruct the sequence of nodes that form it.

    CitadelSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in implementing deterministic game-state logic and compact binary representations, specifically array manipulation and merge semantics for 2048 slide operations plus bit-level packing/unpacking of 4-bit exponent fields.

    CitadelSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates algorithmic problem-solving skills, specifically understanding sorting under constrained inputs and rigorous time and space complexity analysis.

    CitadelData ScientistCoding & AlgorithmsOnsite
  • Design an algorithm to maintain and extract the top-K largest elements in descending order for each sliding window of size W across an array.

    CitadelSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Compute cumulative no-intercept regression slopes as paired data arrives in batches. Reuse running cross-products and sums of squares instead of refitting all historical rows.

    CitadelData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of data structure fundamentals, specifically hash map internals (hashing, collision resolution strategies, load factor, and resizing), time complexity analysis for search/insert/delete, contrasts between arrays and linked lists for random access and insertion, and typical use cases and complexities for stacks versus queues. It is commonly asked in technical interviews to assess algorithmic thinking and the ability to reason about performance trade-offs and appropriate data structure selection; domain: Coding & Algorithms; level: tests both conceptual understanding and practical application.

    CitiSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates implementing and manipulating a line-based document through sequential event processing, emphasizing array/list operations, string handling, and state management; it belongs to the Coding & Algorithms domain and tests data-structure and input-event processing competency.

    ClickupSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of frequency counting, top-K selection, streaming and sliding-window algorithms and data-structure design in the Coding & Algorithms domain, testing both conceptual algorithmic reasoning and practical implementation skills.

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates data modeling with enums, efficient data structure selection to meet specified time complexities, API design for CRUD operations, and practical implementation skills including a command-line interface and unit testing.

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design an efficient in-memory storage manager that handles concurrent file operations, user-based quotas, and data eviction policies.

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A CloudKitchens software-engineer technical screen: build a point-of-sale order that prints an itemized receipt on every item tap, then extend it to apply combo discounts. It tests cart data-structure design, receipt formatting, and the algorithm for selecting a valid set of non-overlapping combos.

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates concurrency and synchronization skills, including thread-safe design, inter-thread communication, state tracking, and correctness properties such as race-condition avoidance and deadlock freedom.

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in text parsing, hierarchical data modeling, tree construction and serialization, string manipulation, and algorithmic complexity (linear time/space).

    CloudKitchensSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design and implement a multi-rule rate limiter that tracks client request quotas across matching path prefixes using a sliding time window.

    CloudflareSoftware EngineerCoding & AlgorithmsOnsite
  • Build a versioned key-value store whose reads return the value a key held at a given timestamp: the latest write at or before that time, or an empty string if there is none. Tests choosing a per-key data layout that keeps point-in-time lookups fast across up to 200,000 operations.

    Cockroach LabsSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in string and array manipulation, ordering by key metrics (string length), and handling tie-breaking via stable ordering, situated in the Coding & Algorithms domain.

    CodeiumSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding of streaming algorithms and dynamic data structures for maintaining order statistics, along with analysis of time complexity and memory trade-offs.

    CognitivMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Given a digit string containing at least one 5, delete exactly one 5 so the remaining string has the largest possible numeric value, keeping any leading zeros. This intern online-assessment problem tests reasoning about how each digit position affects a number and careful handling of repeated digits.

    CohereSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to implement common sequence decoding strategies used in large language models by manipulating token probability distributions.

    CohereMachine Learning 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 Analyze food-delivery data states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to simulate a state-based movement process and calculate cumulative distance based on a non-monotonic set of instructions.

    CoinbaseSoftware 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 Count users over n connections states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    CoinbaseSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skills in designing and implementing in-memory data structures, TTL-based expiration, lexicographic prefix scans, and backup/restore snapshot semantics within the Coding & Algorithms domain.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding of state management and finite-state machines, API design for lifecycle control, and implementation of in-memory data structures and transition validation in the Coding & Algorithms category.

    CoinbaseSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design order stream with state transitions 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.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's skill in sequence pattern recognition, algorithm design, complexity analysis, and robust integer arithmetic by requiring inference among arithmetic, alternating-difference, geometric, and Fibonacci-plus-constant models while tolerating at most one corrupted term under O(n) time and O(1) extra space constraints.

    CoinbaseData ScientistCoding & AlgorithmsHR Screen
  • This question evaluates understanding of combinatorics, deterministic pseudo-random generation, and efficient enumeration for producing unique NFT metadata, measuring competency in algorithm design, state-space management, and handling large-scale outputs.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of weighted random sampling, efficient data structures for maintaining and updating prefix sums, probabilistic reasoning about sampling distributions, and reproducible testing of randomized algorithms within the Coding & Algorithms domain.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite
  • Generate constrained NFT metadata 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.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of iterator design, lazy evaluation, composable higher-order combinators (map, filter, zip, take, drop, chain), edge-case handling for forward/backward and negative-step ranges, overflow-safe termination, peekable semantics, iterator invalidation rules, and writing boundary-focused unit tests.

    CoinbaseSoftware EngineerCoding & AlgorithmsOnsite

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