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Coding & Algorithms Interview Questions

Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.

9403
Questions
546
Companies
11
Topics
8
Languages

Showing 1111–1140 of 1706 results

  • Otter.AiEasySoftware Engineer
    Validate Password Against Multiple Rules

    This problem tests your ability to efficiently iterate through a string while maintaining multiple state-based flags to satisfy diverse validation criteria.

    Coding & AlgorithmsTechnical ScreenStringsValidationAlgorithms
  • PDT PartnersMediumMachine Learning Engineer
    List All Positive Divisors of an Integer in Ascending Order, Then Beat Square-Root Time

    Given a positive integer up to one trillion, return every positive divisor in ascending order, each listed once. The task tests divisor enumeration, correct handling of perfect squares and 64-bit values, and a follow-up asking whether the running time can grow more slowly than the square root of n.

    Coding & AlgorithmsTechnical Screen
  • PalantirMediumSoftware Engineer
    Group employees by shared interests

    This question evaluates a candidate's competency in organizing and querying collections, mapping relationships between entities, and reasoning about algorithmic time and space complexity within data structures and grouping operations.

    Coding & AlgorithmsTechnical Screen
  • PalantirEasySoftware Engineer
    Merge K Individually Sorted Integer Arrays Into One Sorted Array

    Merge k integer arrays, each sorted in non-decreasing order, into one sorted array that keeps every duplicate. The interviewer asked for the two-pointer method and divide and conquer, so the problem tests merging sorted sequences and how the cost grows with the number of arrays.

    Coding & AlgorithmsTechnical Screen
  • PalantirMediumSoftware Engineer
    Simulate a Growing Snake on a Grid and Report the Score After Every Move

    Simulate a snake moving on a rectangular grid, eating food that appears one piece at a time, and return the score after every move or -1 once the snake leaves the board or runs into itself. It tests precise state simulation, collision rules around the moving tail, and efficient tracking of the snake's body.

    Coding & AlgorithmsTechnical Screen
  • Palo Alto NetworksMediumSoftware Engineer
    Find minimum tanks to cover all houses

    This question evaluates a candidate's proficiency in algorithm design, specifically greedy strategies and string/array manipulation for coverage and optimization under local adjacency constraints.

    Coding & AlgorithmsTechnical Screen
  • ParadromicsMediumSoftware Engineer
    Compute ways to climb n steps

    This Coding & Algorithms question evaluates recursion and dynamic programming concepts by asking for the count of distinct ways to climb n steps, framed at an algorithmic/implementation level. It is commonly asked because it probes recognition of overlapping subproblems and the ability to optimize naive recursive approaches through subproblem reuse and improved time/space efficiency.

    Coding & AlgorithmsTechnical Screen
  • ParadromicsMediumSoftware Engineer
    Implement a hash table with put/get

    This question evaluates implementation and design skills for hash-based data structures, testing competency in data structures, hashing, collision handling, and achieving expected O(1) put/get performance in the Coding & Algorithms domain.

    Coding & AlgorithmsTechnical Screen
  • PatreonMediumSoftware Engineer
    Analyze Reports in a Nested Org Chart

    This problem tests your ability to model hierarchical tree structures and use post-order traversal to aggregate data across deep organizational levels efficiently.

    Coding & AlgorithmsTechnical ScreenTreesGraphsRecursion
  • PatreonEasySoftware Engineer
    Design org chart lookup with preprocessing

    This question evaluates skills in data structures and algorithms, specifically tree/forest representation, aggregation of subtree metrics, dynamic updates, and rigorous time and space complexity analysis.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Assess HashMap vs ConcurrentHashMap

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Assess HashMap vs ConcurrentHashMap states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Compare final, finally, finalize

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compare final, finally, finalize states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Compare write-back vs write-through caches

    This question evaluates understanding of caching policies and memory/storage hierarchy trade-offs, focusing on how write-back and write-through handle writes, coherence, durability, latency, bandwidth, dirty bits, write amplification, and power-loss risks.

    Coding & AlgorithmsTechnical Screen
  • PayPalHardData Scientist
    Compute Variance from a Python List

    This question evaluates understanding of basic statistical concepts and numerical computation—specifically population versus sample variance—and tests algorithmic implementation skills, edge-case handling, and complexity reasoning within the Coding & Algorithms domain.

    Coding & AlgorithmsTechnical Screen
  • PayPalEasyData Scientist
    Compute variance of a list in Python

    This question evaluates understanding of statistical measures and numeric computation, focusing on implementing variance calculations (population vs sample) and considerations for numerical stability.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Contrast TCP vs UDP; detect loss

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Contrast TCP vs UDP; detect loss states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Explain HashMap internals and collisions

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Explain HashMap internals and collisions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Explain Java volatile semantics

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Explain Java volatile semantics states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PayPalHardData Scientist
    Explain differences between Python list and tuple

    Evaluates understanding of Python data structures—specifically lists versus tuples—by probing concepts such as mutability and its implications, high-level performance and memory trade-offs, typical use cases, and hashability for use as dictionary keys.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Find k most frequent in linear time

    This question evaluates a candidate's ability to design and analyze efficient frequency-counting algorithms and related data structures, testing competencies in hashing, bucket-based grouping, heap usage, and time/space complexity reasoning.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumData Scientist
    Implement sliding-window device anomaly

    This question evaluates understanding of streaming algorithms, sliding-window state management, per-user data structures, and handling out-of-order events under strict time and space complexity constraints.

    Coding & AlgorithmsTechnical Screen
  • PayPalMediumSoftware Engineer
    Solve common search/parse/graph frequency tasks

    This problem tests your ability to perform a binary search on a rotated sorted array and subsequently count occurrences of elements to identify the top-k most frequent items.

    Coding & AlgorithmsTechnical ScreenBinary SearchHash TableHeap
  • PeregrineMediumSoftware Engineer
    Fetch, group, and print paginated activities

    This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Fetch, group, and print paginated activities states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    Coding & AlgorithmsTechnical Screen
  • PermitflowMediumSoftware Engineer
    Distinguish Permit Requirement Outcomes

    This problem tests your ability to model state transitions based on complex rule sets and implement efficient logic to resolve status precedence when multiple criteria are met.

    Coding & AlgorithmsTechnical ScreenAlgorithmsLogicSet Theory
  • PerplexityMediumSoftware Engineer
    Design a CreditTracker with expirations

    This question evaluates a candidate's ability to design and implement data structures and algorithms for managing time-bound resources with non-monotonic (out-of-order) operations, emphasizing correctness and efficiency within the coding & algorithms domain.

    Coding & AlgorithmsTechnical Screen
  • PerplexityMediumSoftware Engineer
    Implement Dependency-Aware To-Do List

    Design an in-memory task management system that tracks directed dependencies between tasks, prevents cycles, and unblocks dependent tasks upon completion.

    Coding & AlgorithmsTechnical ScreenGraphDesignTopological Sort
  • PerplexityMediumData Scientist
    Implement Stratified Sampling by Country

    Implement proportional stratified sampling on an in-memory list of records partitioned by a categorical key, ensuring exact sample size via the largest remainder method and reproducible selection.

    Coding & AlgorithmsTechnical Screenalgorithmsstatisticssampling
  • PerplexityHardSoftware Engineer
    Implement Task Dependencies and Failure

    This question evaluates understanding of graph-based data structures and algorithms for modeling bidirectional task dependencies, status tracking, and efficient cascading failure propagation in an in-memory task manager.

    Coding & AlgorithmsTechnical Screen
  • PikaHardSoftware Engineer
    Evaluate Spreadsheet Cells and Reject Circular References

    Implement a small spreadsheet whose cells hold integers or single-reference formulas with offsets. Evaluate through current dependencies, propagate updates, report unset chains, and reject a formula atomically whenever it would introduce a circular reference.

    Coding & AlgorithmsTechnical Screen
  • PilotEasySoftware Engineer
    Solve Anagram Without Sorting

    This question evaluates proficiency in string manipulation, character frequency analysis, and asymptotic time/space complexity reasoning. It is commonly asked in the coding & algorithms domain to test practical application of basic data structures (string processing and frequency-based counting), correctness under input constraints, and the ability to design efficient, linear-time solutions rather than purely conceptual reasoning.

    Coding & AlgorithmsTechnical Screen