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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 901–930 of 3276 results

  • Find the starting index of the first substring of a text that is a rearrangement of a given pattern, or report that none exists. Tests fixed-length sliding windows, character-frequency bookkeeping and linear-time scanning of long strings with an early exit.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manipulate binary representations of IP addresses and perform efficient prefix matching using CIDR notation, requiring careful bitwise arithmetic and efficient lookup structures.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Given a city grid with a start, a destination and cells usable by only one of four commute modes, choose the mode whose trip takes the least total time, breaking ties by lower total cost. Tests shortest-path search on grids, per-mode reachability and precise tie-breaking.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in string processing, character-frequency analysis, and efficient substring search techniques, measuring competency in algorithmic reasoning and implementation for pattern matching.

    DatabricksBackend EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to map nodes in a recursively defined tree structure without materializing the tree, requiring an understanding of Fibonacci sequences and path-finding algorithms in binary trees.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to efficiently detect pattern matches within a stream or string using a sliding window technique and frequency mapping.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of IPv4 and CIDR notation, ability to perform prefix-based address containment checks using bitwise reasoning, and competence in parsing and efficient lookup across many ranges.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to aggregate per-customer revenue from event streams and perform selection on aggregated totals, testing knowledge of data aggregation, selection algorithms, and efficient use of data structures.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to navigate implicit tree structures defined by recurrence relations and your proficiency in pathfinding within large graphs without materializing them.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of recursive binary tree structures, preorder indexing, Fibonacci-like size relations, and arithmetic-based navigation for computing paths in an implicitly defined tree.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an ordered first-match IPv4 firewall that returns ALLOW or DENY for an address, then extend it so the target can be a whole CIDR block that is allowed only if every address inside it is. Tests bit-level prefix matching and reasoning about address ranges at scale.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • Implement tic-tac-toe on an m by n board where a player wins with k consecutive marks in a row, column or either diagonal, returning the winner after each move. Tests incremental win detection that avoids rescanning the board, plus careful handling of edges and both diagonal directions.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Implement CIDR firewall matcher states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design and implement a generalized m x n Tic-Tac-Toe game supporting an arbitrary winning streak length k. Tests grid simulation, efficient line checking around the latest move, and handling boundary conditions.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates data-structure design and iterator semantics—specifically snapshot iteration over a mutable, set-like collection without order guarantees—and tests skills in implementing mutation-isolated iteration and analyzing time and space complexity; it belongs to the Coding & Algorithms domain and emphasizes practical implementation.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of set data structures, iterator and snapshot semantics, and the ability to reason about time and space complexity when providing stable views over mutable collections.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design a state-tracking system for an n x n Tic-Tac-Toe board that allows for constant-time move validation and win detection.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of designing efficient time-windowed data structures and algorithmic analysis, including space-time trade-offs and amortized complexity.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of time-based data structures and algorithms for sliding-window counters, including fixed-size array bucketing, handling timestamp collisions within buckets, refactoring for reuse, and time/space complexity analysis.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of persistent/versioned data structures, iterator semantics, concurrency control, and complexity-aware design for mutable sets, and is categorized under Coding & Algorithms.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a robust state machine for a board game, focusing on efficient win-condition checking and clean API design.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to implement lazy computation using function composition and design a stateful data structure with metadata tracking.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency in string manipulation and encoding algorithms, specifically run-length encoding and decoding, along with attention to edge cases such as empty inputs and single-character runs and correct handling of repetition counts.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of data compression algorithms, bit-level manipulation, two's‑complement integer representation, streaming algorithm design, and encoder/decoder state management for 32-bit signed integers.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • Tests the ability to solve multi-source shortest path problems on a grid using multi-source Breadth-First Search (BFS). Evaluates graph traversal efficiency, boundary checking, and handling of impassable terrain.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manipulate an Abstract Syntax Tree (AST) representing a relational query plan to reduce data processing costs through predicate pushdown and projection pruning.

    DatabricksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Determine the minimum number of contiguous substrings from a source string required to reconstruct a target string.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • Given the order of a recursively defined Fibonacci tree and two nodes labeled by preorder number, return the path between them without building a tree that can hold trillions of nodes. Tests recursive subtree-size reasoning, implicit tree navigation and 64-bit index arithmetic.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • Build a referral credit tracker with account creation, threshold queries, deterministic ordering, and correct credit propagation through indirect referrals.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite
  • Process a sequence of alternating tic-tac-toe moves on an n x n board and report, after every move, whether player 1 or player 2 has just completed a full row, column, main diagonal or anti-diagonal. Tests efficient incremental win detection, diagonal indexing and correct handling of draws.

    DatabricksSoftware EngineerCoding & AlgorithmsOnsite

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