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Coding & Algorithms interview questions

3276 Coding & Algorithms questions from 366 companies, with hints, runnable code and solution walkthroughs.

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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 301–330 of 3276 results

  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Solve three coding tasks: binary search, tree path, subarray states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This pair of problems evaluates proficiency with tree data structures and traversal concepts (deepest shared ancestor) and with dynamic programming/state optimization on linear arrays (maximizing non-adjacent house values), assessing algorithmic reasoning, complexity awareness, and data-structure manipulation.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in data-structure manipulation (set operations, mapping and deduplication), directed-graph modeling and traversal for reachability, and algorithmic time/space complexity analysis.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This question set evaluates string-processing and algorithmic problem-solving skills, including encoding and transformation for unique representations and dynamic programming, memoization, and backtracking for enumerating all valid segmentations.

    AmazonData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates array and hashing algorithms, pair-sum reasoning including duplicate handling and lexicographic minimality, streaming and external-memory algorithm design, trade-offs in time/space complexity, and extension to three-sum with deduplication.

    AmazonData ScientistCoding & AlgorithmsOnsite
  • Design a simplified in-memory spreadsheet supporting direct cell assignment, formula assignment (summation with potential duplicate cell references), and retrieval with dynamic dependency propagation.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • Phone screen coding problem: process push and pop operations on a stack in which every pop removes the value that currently occurs most often, breaking ties by the tied value closest to the top. It tests designing a data structure that tracks frequency and recency together efficiently.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests the ability to track a range of sequential integers and identify gaps in a stream of incoming data using efficient data structures.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manage sparse, out-of-order data using data structures like sets or priority queues and finding gaps within a contiguous range.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests state-space dynamic programming by unifying different stock trading constraints (transaction limits and per-transaction fees) into a single optimized state-transition model.

    AmazonSoftware 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 Validate 9x9 grid in one pass states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    AmazonSoftware EngineerCoding & AlgorithmsOnsite
  • Tests understanding of basic data structures—specifically stacks—to validate balanced and nested bracket sequences in linear time.

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to model prerequisites as a directed graph and detect circular dependencies using cycle detection algorithms (Kahn's or DFS).

    AmazonSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A coding problem about a fixed-length integer array that supports point updates, numbered snapshots of the whole array, and reads of any position as of an earlier snapshot, processed as a list of operations. It tests designing a versioned data structure that stays fast and memory-efficient when snapshots are frequent.

    AmazonSoftware EngineerCoding & AlgorithmsOther
  • Design a least-recently-used cache 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.

    Ambience HealthcareSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Maximize point coverage with an axis-aligned rectangle under a perimeter budget, including boundary points and repeated coordinates.

    AmericanSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Calculate the minimum number of orthogonal moves needed to distribute stones so that every cell in a 3x3 grid contains exactly one stone.

    AmericanSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Render bordered and filled rectangles onto a fixed ASCII canvas, clipping safely and honoring input-order overwrites. Handle negative coordinates, fully hidden shapes, one-cell dimensions, trailing spaces, overlap behavior, and a canvas of up to one million cells.

    AmperitySoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates recursion, graph traversal and cycle-detection concepts for hierarchical employee validation alongside state management, event-driven input handling and collision detection for a grid-based Snake game.

    AmplitudeSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates a candidate's understanding of singly linked list pointer manipulation, in-place node swapping with O(1) extra memory, and handling of edge cases such as when the k-th node from the end is the head.

    AmplitudeSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to maintain a dynamic set of scores and efficiently query the rank of a user, requiring a balance between update complexity and retrieval time.

    Anchorage DigitalSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to recursively traverse a tree structure and format the output into a specific, ordered directory-style string representation.

    Anchorage DigitalSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design an in-memory index that supports dynamically inserting words and checking whether any previously inserted word ends with a given suffix in time proportional to the suffix length.

    AndurilSoftware EngineerCoding & AlgorithmsOnsite
  • Implement a variadic prefix expression evaluator supporting addition and left-associative subtraction with support for nested expressions and error handling.

    AndurilSoftware EngineerCoding & AlgorithmsOnsite
  • Implement a simplified mark-and-sweep sweep phase to identify unreferenced heap objects given a list of heap allocations and stack root pointers.

    AndurilSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a mark-phase reachability analysis for a heap graph starting from stack roots, returning unreachable heap addresses in their original order while handling cycles, self-references, and dangling pointers.

    AndurilSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests dynamic programming and optimization skills by requiring the calculation of the maximum profit obtainable from cutting a rod into integer-length pieces with given price values.

    AndurilSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in string data structures and manipulation (prefix-search concepts including case-insensitive matching and regex-based normalization) as well as linked list pointer manipulation and in-place node removal.

    AnsysSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Design a data structure that tracks time-limited credit grants, prioritizes consuming grants that expire earliest, and efficiently manages expired funds.

    AnthropicSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates proficiency with bitwise operations, branchless programming, low-level performance optimizations, and microarchitectural reasoning about pipeline stalls, instruction-level parallelism, and cache behavior.

    AnthropicSoftware EngineerCoding & AlgorithmsOnsite

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