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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 2821–2850 of 3276 results

  • This question evaluates understanding of kinematics, motion modeling, and numerical reasoning for safety-critical control logic, focusing on stopping-distance computation and the impact of reaction time on braking decisions.

    TeslaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving with arrays and analysis of time-space trade-offs in the Coding & Algorithms domain, and is commonly asked to assess a candidate's ability to transform brute-force approaches into efficient linear-time solutions while reasoning about memory usage.

    TeslaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests matrix traversal techniques, specifically using DFS/BFS to identify connected components and multi-source BFS to find the shortest path between them.

    TeslaSoftware EngineerCoding & AlgorithmsOnsite
  • This multi-part question evaluates algorithmic problem-solving and data-structure competency, covering expression parsing, array and sequence manipulation, sorting-based counting, interval merging, graph traversal/union-find, in-place rearrangement, hashing for set operations, and DAG/topological ordering within the Coding & Algorithms domain.

    TeslaSoftware EngineerCoding & AlgorithmsHR Screen
  • This question tests the ability to handle window functions for running totals and conditional aggregation to transform raw manufacturing logs into formatted monthly production reports.

    TeslaData EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manage state and look-ahead logic when processing a sequence of events (bowling rolls) governed by specific conditional scoring rules.

    The Trade DeskSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's ability to implement an in-memory cloud storage system, exercising skills in data structures and stateful API design, string handling and pattern matching, sorting and eviction algorithms, and per-user resource accounting.

    The Trade DeskSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates proficiency with piecewise-linear interpolation on strictly increasing (monotonic) arrays, sound handling of out-of-range queries (error, clamp, extrapolate, or None/NaN), and efficient interval search over sorted data with a target of O(log n). It also probes real-world judgment about when each out-of-range policy is appropriate and which non-bisect strategies exist.

    The Trade DeskData ScientistCoding & AlgorithmsTechnical Screen
  • This question tests practical coding ability in probabilistic simulation, requiring implementation of a Monte Carlo method to estimate conditional win probabilities under two decision strategies. It assesses a data scientist's skill in translating a classic probability scenario into working randomized code rather than relying on closed-form analysis.

    ThumbtackData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates implementation skills in basic descriptive statistics (min, mean, median), numerical stability in online aggregation methods, robust handling of edge cases like None/NaN and extreme numeric ranges, and algorithmic complexity reasoning in the Coding & Algorithms domain for a Data Scientist role.

    ThumbtackData ScientistCoding & AlgorithmsOnsite
  • This question evaluates understanding of graph search algorithms, heuristic properties (admissibility and consistency), path optimality and time/space complexity, requiring application of BFS, uniform-cost search, A*, and DFS on a concrete weighted graph.

    TikTokData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates data manipulation and aggregation skills, focusing on handling duplicate values within collections and computing numerical summaries of list data.

    TikTokData ScientistCoding & AlgorithmsOnsite
  • Compute city skyline silhouette 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.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of subsequences, dynamic programming and algorithmic optimization for array processing, and is categorized under Coding & Algorithms; it emphasizes practical application of algorithm design and complexity analysis rather than purely theoretical knowledge.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to optimize path calculations in a non-linear data structure using dynamic programming, specifically focusing on space complexity optimization.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of graph algorithms and dependency resolution, specifically topological sorting and cycle detection, along with competence in choosing appropriate data structures and analyzing time/space complexity.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency with array manipulation, parity-aware summation, and combinatorial counting when elements are removed, situating it in the Coding & Algorithms domain.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests grid traversal (DFS/BFS) and the ability to represent spatial structures in a canonical form to identify unique patterns.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skills in graph and grid algorithms, topology-aware adjacency (torus wrap-around), and maintaining dynamic connectivity under incremental updates.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to optimize subarray sum calculations from an O(n^2) approach to O(n) using a hash map for prefix sum tracking.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in mutable data structure operations, specifically linked list node removal and binary tree node replacement/deletion, requiring knowledge of traversal, pointer/reference manipulation, and edge-case handling.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's understanding of data structures and algorithm design, specifically skills in implementing constant-time cache operations, eviction policies, update handling, and concurrency/thread-safety considerations.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates dynamic programming, state-space reachability, and constrained transition reasoning, along with skills in hash-based memoization and time/space complexity analysis.

    TikTokMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of dynamic programming and string-processing skills, along with algorithmic complexity analysis for segmentation problems.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Differentiate virtual and pure virtual functions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of Java framework internals and related competencies including dependency injection, aspect-oriented programming and proxy mechanisms, transaction management, annotation processing, bean lifecycle, classpath scanning, bean scopes, and circular dependency detection or resolution.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to model dependencies as a directed graph and determine a valid sequence using topological sorting (Kahn's algorithm or DFS).

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Find and count target-sum subarrays 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.

    TikTokMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates mastery of searching algorithms and algorithmic complexity analysis, particularly the ability to locate boundary positions within a sorted array.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving and data-structure reasoning, focusing on order statistics and operations on a row- and column-sorted matrix within the Coding & Algorithms domain.

    TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen

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