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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 2221–2250 of 3276 results

  • This question evaluates competency in real-time event stream processing, per-button state management, and timing-based classification of input events such as distinguishing single versus long presses.

    OtherSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in bitwise arithmetic, integer overflow semantics, sign handling, and algorithmic efficiency for implementing multiplication without using multiplication or division operators.

    OtherData ScientistCoding & AlgorithmsTechnical Screen
  • Find the lowest common ancestor in a binary tree using explicit child arrays, including identical targets, ancestor targets, and deep trees.

    OtherSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates randomized and streaming algorithm skills, including mastery of reservoir sampling, induction-based correctness proofs, probability reasoning, and complexity analysis for sampling under strict memory constraints.

    OtherData ScientistCoding & AlgorithmsOnsite
  • This question evaluates combinatorics, array manipulation, and space-efficient algorithm design by requiring computation of a specific row of Pascal’s triangle without constructing the full triangle.

    OtherSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Implement spreadsheet formulas with dependency updates, repeated references, unset cells, and cycle detection that recovers after formulas change.

    OtherSoftware EngineerCoding & AlgorithmsOther
  • Implement worker sessions, current metadata, promotions, ordered filtering, and time-clipped compensation with historical rates and non-stacking double-pay intervals.

    OtherSoftware EngineerCoding & AlgorithmsOnline Assessment
  • Validate nested parentheses, brackets, and braces with correct handling of empty input, mismatched closing symbols, and unfinished groups.

    OtherSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding and implementation of optimization algorithms for machine learning, specifically mini-batch gradient descent, and measures competency in numerical optimization, algorithmic implementation, and training dynamics within the Coding & Algorithms domain for Data Scientist roles.

    OtherData ScientistCoding & AlgorithmsOnsite
  • This question evaluates understanding of tree data structures and ancestor-walk queries, assessing competency in traversing rooted trees, interpreting parent arrays, and designing efficient query-processing methods for large n and q.

    OthersData ScientistCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to optimize ancestor lookups in a tree using the Binary Lifting technique to achieve logarithmic query time.

    OthersSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to parse and evaluate a string representing a mathematical expression with basic operator precedence, typically requiring a stack-based approach or a recursive descent parser.

    Otter.AiSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Given an array of positive integers, find the fewest operations that make every element 1, where each operation replaces one of two neighboring values with their greatest common divisor, or return -1 if it cannot be done. Tests GCD properties, lower-bound reasoning and careful case analysis on small arrays.

    Otter.AiSoftware EngineerCoding & AlgorithmsOnsite
  • This question tests a candidate's ability to implement greedy line-packing and space-distribution algorithms, core string manipulation skills evaluated in software engineering interviews. It assesses practical application of text layout logic, including handling edge cases like single-word lines and justified formatting with uneven space distribution.

    Otter.AiSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to parse and evaluate mathematical expressions containing non-negative integers, addition, subtraction, multiplication, and nested parentheses using a stack-based approach or recursion.

    Otter.AiSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the ability to implement a nested transactional key-value store using stack-based state management and scope shadowing.

    Otter.AiSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to efficiently iterate through a string while maintaining multiple state-based flags to satisfy diverse validation criteria.

    Otter.AiSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to manage and reuse resources efficiently using data structures that allow for logarithmic time allocation and deallocation within partitioned namespaces.

    OuraSoftware EngineerCoding & AlgorithmsOnline Assessment
  • 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.

    PDT PartnersMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Implement a checkout calculation engine that applies item-specific coupons to cart lines using exact banker's rounding (round-half-to-even) per unit and returns the final cart total in integer cents.

    PalantirSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates understanding of graph data structures and shortest-path concepts, including correct modeling of undirected edges, unweighted versus weighted pathfinding, and algorithmic time and space complexity.

    PalantirSoftware EngineerCoding & AlgorithmsOnsite
  • 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.

    PalantirSoftware EngineerCoding & AlgorithmsTechnical Screen
  • 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.

    PalantirSoftware EngineerCoding & AlgorithmsTechnical Screen
  • 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.

    PalantirSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a cart checkout calculator that stacks item and category discounts multiplicatively, caps savings at 80%, and applies round-half-up once per item.

    PalantirSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates algorithmic problem-solving and data structure proficiency in computing the maximum rectangular area within a histogram-like array, focusing on contiguous segment analysis and range-based aggregation.

    Palo Alto NetworksSoftware EngineerCoding & AlgorithmsOnsite
  • 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.

    Palo Alto NetworksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates competency in computing normalized list differences, including string normalization, collection comparison, duplicate handling, and time and space complexity reasoning.

    Palo Alto NetworksSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of binary tree manipulation and traversal methods, emphasizing recursion and iterative approaches as well as the ability to reason about time and space complexity.

    Palo Alto NetworksSoftware EngineerCoding & AlgorithmsOnsite
  • 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.

    ParadromicsSoftware EngineerCoding & AlgorithmsTechnical Screen

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