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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 1591–1620 of 3276 results

  • This question evaluates proficiency in graph algorithms, shortest-path computation, and algorithmic optimization when augmenting a directed weighted graph with additional unit-weight edges.

    MathWorksSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to handle currency conversion using graph pathfinding (multiplicative weights) and implement a custom pagination algorithm that balances item distribution while respecting original ordering.

    MavenclinicSoftware EngineerCoding & AlgorithmsOnsite
  • Parcels arrive one at a time for a bank of numbered lockers, each requesting a preferred locker and overflowing to the next higher-numbered empty one if it's taken. Decide whether every parcel finds a locker. Tests precise rule-following and an efficient alternative to simulating forward scans one slot at a time.

    MercorMachine Learning EngineerCoding & AlgorithmsOnsite
  • Given a list of pairwise currency exchange rates such as USD to GBP at 0.77, compute the rate from a source currency to a target currency, converting through intermediate currencies and using rates in reverse where needed. It tests reasoning about chained conversions, unknown or unreachable currencies, and a clear time and space complexity analysis.

    MercorSoftware EngineerCoding & AlgorithmsOnsite
  • Design and implement an in-memory referral network as a directed acyclic graph (DAG) supporting cycle-safe edge insertion, depth-bounded reachability queries, and expected reward computation under geometric decay.

    MercorMachine Learning EngineerCoding & AlgorithmsOnsite
  • This question tests your ability to apply Breadth-First Search (BFS) on an augmented state space where path state includes both coordinates and remaining resources.

    MercorSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Add two non-negative integers that are given as decimal digit strings, possibly thousands of digits long, and return the sum as a string without converting to built-in numbers. Tests digit-by-digit addition with carries, inputs of unequal length and canonical output without leading zeros.

    MetaSoftware EngineerCoding & AlgorithmsOther
  • Preprocess a sorted array derived from a static BST to answer many inclusive range queries. Use binary-search boundaries and wide prefix sums to return both the sum and count for each range without rescanning the tree.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This set of four problems evaluates algorithmic competencies including ASCII string processing and character classification, array transformation and operation-count reasoning, cost-minimization for enforcing monotonicity under only-increase constraints, and time-based simulation of resource scheduling with recharge cycles.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manipulate graph-like data structures to perform neighbor analysis and efficient set operations to rank potential connections.

    MetaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates web API development and backend engineering competencies, including FastAPI usage, Python type hints, Pydantic-based request/response validation, error handling, in-memory state management, and modular router/service/model layering, and it belongs to the Coding & Algorithms category with a focus on backend web service and API design. It is commonly asked to assess practical ability to deliver production-ready REST endpoints with proper validation and error handling under constrained resources, and the level of abstraction required is primarily practical implementation with attention to architectural design.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to implement a graph-based recommendation algorithm using common neighbors and popularity constraints to rank potential connections.

    MetaMachine Learning EngineerCoding & AlgorithmsOnsite
  • Convert an absolute Unix-style file path into its canonical form by collapsing repeated slashes, dropping single-dot segments, resolving double-dot segments against the parent directory, and treating other dot sequences as ordinary names. It tests careful string parsing and edge cases such as the root directory.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • Determine whether a string can be transformed into a palindrome by removing at most k characters. Tests dynamic programming, palindrome properties, and recursive search with branch bounding.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • Decide whether an abbreviation made of lowercase letters and decimal skip counts matches a given word, where each number skips that many characters and any number with a leading zero is invalid. It tests careful string scanning, multi-digit number parsing and end-of-input boundary checks.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of array and matrix manipulation, sliding-window and streaming statistics, and appropriate data-structure choices for maintaining aggregates and order-statistics such as moving averages and sliding-window medians.

    MetaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates skill in matrix manipulation and algorithmic reasoning, specifically understanding diagonal traversal, equality checks, and handling boundary conditions such as empty matrices, single-row or single-column inputs, and negative values.

    MetaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the ability to optimize a two-step decision process by maintaining track of the best previous state, requiring a linear scan approach.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • Tests bitmask representation, backtracking with pruning, and combinatorial optimization under character-uniqueness constraints.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • Meta software-engineer technical-screen coding question: deep-copy a singly linked list whose nodes carry an arbitrary random pointer (which may be null, point backward, or form cycles). It tests both the O(n)-space hash-map solution and the O(1)-auxiliary-space in-place weaving technique, plus reasoning about pointer integrity, cycle safety, and verifying the copy is structurally equal to and isolated from the original.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • A coding question asking you to merge many integer arrays, each already sorted in non-decreasing order, into a single sorted array that keeps every duplicate value. It tests multi-way merging, efficiency as the number of input arrays grows, and edge cases such as empty inputs and arrays of different lengths.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates understanding of binary search tree properties, traversal techniques, and the ability to implement both recursive and iterative algorithms while reasoning about time and space complexity.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to manage state in nested processes using a stack data structure to track the exclusive execution time of functions based on a log of start and end events.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This Coding & Algorithms question in the Data Engineer domain evaluates grouping and top‑k aggregation concepts, testing the ability to combine per-category aggregation with selection under a uniqueness constraint.

    MetaData EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to trade preprocessing time for query performance using prefix sum arrays to efficiently calculate the sum of elements within a specified range.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question tests the ability to implement a sliding window algorithm to compute the average of contiguous subarrays, emphasizing optimization of time complexity.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • Compute maximum stock profit for both one transaction and unlimited nonoverlapping transactions in linear time, returning zero when no positive trade is available.

    MetaSoftware EngineerCoding & AlgorithmsOnsite
  • This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Compute binary tree diameter states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving with binary trees, focusing on tree traversal techniques, recursion versus iterative implementations, and analysis of time and space complexity including worst-case input shapes such as skewed trees.

    MetaData ScientistCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to manipulate nested dictionary data structures and perform aggregate capacity computations, assessing data transformation, mapping, and set-based reasoning skills relevant to a Data Engineer within the Coding & Algorithms domain.

    MetaData EngineerCoding & AlgorithmsTechnical Screen

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