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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 2101–2130 of 3276 results

  • This question evaluates competency in implementing an in-memory key-value store with persistence, covering concepts such as serialization, durability, data structure management, and basic I/O handling.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to design a recursive data structure for an abstract syntax tree and implement a unification-based type inference engine for a simple functional language.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a cellular automaton simulating epidemic spread on a 2D grid with simultaneous infection and mortality transitions until convergence.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a toy type-inference engine that unifies generic parameter types with concrete argument types and substitutes resolved type variables to determine the return type.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • Simulate a memory allocator over n units: each allocation takes the leftmost run of consecutive free units for an owner, and each free releases all of that owner's units. Return the result of every operation. It tests interval bookkeeping and logarithmic-time search for free runs at up to 100,000 operations.

    OpenAISoftware EngineerCoding & AlgorithmsOnsite
  • Simulate booking a single theater row of n seats, where each booking takes the leftmost block of consecutive free seats for a group and a cancellation releases every seat that group currently holds anywhere in the row. Tests augmented-interval bookkeeping and logarithmic-time search for the best free run.

    OpenAISoftware EngineerCoding & AlgorithmsOnsite
  • This question evaluates data-structure design and algorithmic reasoning for time-based resource accounting, including handling expiring credits and out-of-order operations while maintaining efficient (logarithmic) performance constraints.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates algorithmic problem-solving skills focused on interval manipulation, sorting and merging logic, and time/space complexity analysis within the Coding & Algorithms domain, emphasizing practical application.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Simulate a row of microorganisms in which each one may eat a strictly smaller neighbor from a different family, with rounds resolved from left to right, and report the family and size of the largest survivor at equilibrium. It tests precise rule-following, list mutation during iteration, and careful per-round bookkeeping.

    OpenAISoftware EngineerCoding & AlgorithmsOnline Assessment
  • This problem tests your ability to simulate a state-based grid propagation and optimize intervention timing using either greedy or dynamic programming approaches.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a developer's skills in C++ performance engineering and concurrent systems, covering profiling, bottleneck identification (e.g., cache locality and lock contention), and code-level performance reasoning to improve throughput and latency.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Return a deterministic, lexicographically smallest valid ordering of named prep steps with dependency constraints, correctly including steps with no prerequisites and steps unconnected to any dependency.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests deterministic topological sorting of a directed acyclic graph using Kahn's algorithm and a priority queue to guarantee lexicographical tie-breaking.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests interval manipulation and greedy optimization by requiring you to adjust a set of shard ranges so that no more than k ranges overlap at any integer point, while minimizing the number of boundaries moved.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests your ability to refactor procedural, error-prone code into a robust, extensible pipeline for parsing and managing chat message state.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Follow single-target redirects from a start code and return the final code, or the last code before the walk would revisit one. Then answer many starts in linear total time. Tests visited-set bookkeeping and functional-graph structure.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement a deterministic topological sort using a min-heap to return the lexicographically smallest ordering of a directed graph, or detect cycles and return an empty list.

    OpenAISoftware EngineerCoding & AlgorithmsOnsite
  • Choose one courier company per day so that no company works two days in a row and the total price is minimal, then return the schedule. Tests DP over a small state, path reconstruction, and the best/second-best trick for k options.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • This problem tests the ability to design an incremental task scheduler that balances workload across a pool of annotators while maintaining fairness and deterministic state transitions.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • Design a search algorithm using state-space exploration to find the minimum number of turns required to defeat a boss given transient health, scripted boss attacks, and a single-use revive.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • Implement a discrete-time cellular automaton simulating epidemic spread on a 2D grid with multi-day infection states, immunity waning, and mortality rules.

    OpenAIMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Implement a cellular automaton simulation modeling disease spread on a 2D grid with discrete cell states and timed recovery.

    OpenAIMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates a candidate's ability to implement discrete-time grid simulations with delayed state transitions, reason about simultaneous updates and neighborhood effects, and perform a limited combinatorial optimization (choosing one row or column) to minimize a global outcome.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a stateful simulation engine that handles turn-based mechanics, complex status modifiers, and dynamic combat interactions.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • This problem tests your ability to design a robust state management system and implement validation logic for a rule-based game.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Tests modeling multi-source breadth-first search (BFS) on a 2D grid to compute simultaneous state propagation across discrete time steps.

    OpenAISoftware EngineerCoding & AlgorithmsTechnical Screen
  • Implement an online, numerically stable algorithm to compute Shannon entropy over an unbounded stream of categorical tokens with O(1) updates.

    OpenAIMachine Learning EngineerCoding & AlgorithmsTechnical Screen
  • Design an in-memory credit ledger to track expiring GPU compute credits, support priority consumption, and manage resource debt.

    OpenAIMachine Learning EngineerCoding & AlgorithmsOnsite
  • This problem tests the implementation of an in-memory key-value store supporting TTL expiration, atomic transactions with rollback capabilities, and logical time-based validation.

    OpendoorBackend EngineerCoding & AlgorithmsTechnical Screen
  • This question evaluates understanding of tree and graph concepts, strict string parsing and validation, duplicate and cycle detection, and the construction of canonical S-expressions within the Coding & Algorithms category.

    OptiverSoftware EngineerCoding & AlgorithmsOnline Assessment

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