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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 1171–1200 of 3276 results

  • This problem tests your ability to optimize interval lookup operations by preprocessing data into an efficient search structure to handle containment queries in sub-linear time.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to normalize input strings by grouping consecutive identical characters and efficiently searching a dictionary for potential word matches.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to efficiently track the connectivity of a graph as edges are added over time, requiring an understanding of Union-Find data structures and graph theory.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Tests interval processing, sorting, and tracking concurrent overlapping ranges using heaps or two-pointer sweep-line techniques.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement algorithms to analyze top-to-bottom paths in a blocked, cell-weighted grid: reachability check, deterministic path enumeration, and minimum-cost path finding with lexicographic tie-breaking.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to optimize search operations across multiple data sources, focusing on minimizing high-latency API calls by using heuristic strategies and efficient state management.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Tests computational geometry and algorithmic efficiency by finding a horizontal line that bisects the total area of non-overlapping rectangles using sweep-line or binary search techniques.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to efficiently match a query string against a dictionary of patterns containing wildcards and determine the best match based on predefined precedence rules.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to navigate tree structures and perform post-order traversal to identify an ancestor node based on a custom aggregate criterion (the minimum value).

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to optimize search operations within a hidden set of dependencies by minimizing calls to a costly black-box oracle.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates computational geometry and algorithm design skills, focusing on area computation, monotonicity reasoning, existence proofs, root-finding under floating-point constraints, and considerations of numerical stability and complexity.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates algorithmic problem-solving with ordered data structures, specifically understanding how to combine two sorted arrays efficiently, priority-queue or merge-based reasoning, and time/space complexity analysis in the coding and algorithms domain.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to reason about digit-based frequency analysis and efficient counting on arrays, testing competencies in combinatorics and algorithmic optimization for grouping elements by shared features.

    GoogleSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This question evaluates a candidate's ability to model pairwise relationships and compute connected components in small graphs, testing skills in graph connectivity and grouping based on shared attributes in arrays of two-digit numbers.

    GoogleSoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to use a sliding window or linear scan approach to identify contiguous subarrays and your capacity to optimize for a single modification to extend an existing sequence.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to design memory-efficient streaming algorithms and parallel processing strategies for extremely large files, covering skills in external-memory algorithms, file I/O, concurrency, and correctness under resource constraints.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to find the median of two sorted, run-length encoded arrays without fully decompressing them, focusing on efficiency and pointer manipulation.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's understanding of tree data structures and frequency analysis, focusing on handling a trinary search tree variant and determining mode values across possibly large datasets.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests knowledge of the sum-of-two-squares theorem and efficient counting of integer partitions into two squares, requiring an understanding of number theory or optimization via circle/grid search.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic reasoning and inference from constrained feedback, testing skills in information-theoretic deduction, pattern matching, and search strategy within a bounded-query interactive setting.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates the ability to design efficient algorithms and data-processing strategies for identifying shared object identifiers across large log files, testing skills in streaming processing, set membership handling, and external-memory algorithm reasoning.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates proficiency in graph traversal and shortest-path computation, including handling nodes that are blocked or that incur additional costs. It is commonly asked in the coding and algorithms domain (graph algorithms) to assess both practical implementation skills and conceptual understanding of complexity, edge cases, and trade-offs between unweighted and weighted path models.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to model a relationship network as a graph and implement Breadth-First Search (BFS) to find the shortest path length between two nodes.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to use the sliding window (two-pointer) technique combined with hash maps to find an optimal subarray satisfying a frequency constraint.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to solve subarray problems using the sliding window (two-pointer) technique and hash maps to track element frequencies.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests greedy algorithms, digit manipulation, and boundary handling to find the largest number less than or equal to n with non-decreasing decimal digits.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Practice a Google coding interview problem focused on find the longest consecutive path in a binary tree. The prompt emphasizes edge cases, clean implementation, and verifiable test behavior without revealing the solution.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Tests array traversal, state tracking, and boundary handling to find the maximum length of a contiguous, strictly increasing run in linear time.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests tree traversal techniques and dynamic programming on trees, specifically how to track path lengths across subtree boundaries using a recursive helper function.

    GoogleSoftware EngineerCoding & AlgorithmsOnsite
  • Tests grid traversal and dynamic programming to find the maximum consecutive sequence of identical elements along horizontal, vertical, and diagonal lines.

    GoogleSoftware EngineerCoding & AlgorithmsTechnical Screen

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