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Coding & Algorithms Interview Questions

Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.

9403
Questions
546
Companies
11
Topics
8
Languages

Showing 961–990 of 3276 results

  • DockerMediumSoftware Engineer
    Evaluate an arithmetic expression

    This problem tests the ability to parse and evaluate arithmetic expressions involving addition, subtraction, multiplication, and division, requiring careful handling of operator precedence and parsing multi-digit integers.

    Coding & AlgorithmsTechnical ScreenStackParsingString Manipulation
  • DocuSignMediumSoftware Engineer
    Collapse runs of adjacent anagrams in a word list

    Given a list of lowercase words, repeatedly delete any word that is an anagram of the word immediately before it, and return what remains in its original order. The task tests anagram comparison, reasoning about how repeated deletions interact, and producing a unique, order-preserving result.

    Coding & AlgorithmsTechnical Screen
  • DocuSignEasySoftware Engineer
    Compress Consecutive Integer Ranges

    Tests array manipulation, sorting, deduplication, and range-grouping logic to produce a compact string representation of consecutive numbers.

    Coding & AlgorithmsOnsitearrayssortingstring
  • DocuSignMediumSoftware Engineer
    Find maximum island sum and required indices

    This question evaluates grid-based graph traversal and connected-component aggregation skills, including handling positive and negative cell values, tie-breaking by row-major indices, and computing maximum component sums.

    Coding & AlgorithmsTechnical Screen
  • DocuSignMediumSoftware Engineer
    Implement a key-value CRUD store

    This question evaluates understanding of core data structures, API design, complexity analysis, and edge-case handling for an in-memory key–value CRUD store, and falls under the Coding & Algorithms domain while testing both practical implementation skills and conceptual reasoning about time/space trade-offs.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Calculate Courier Earnings

    This question evaluates algorithmic problem-solving with emphasis on temporal interval aggregation, handling overlapping events, and applying conditional rate multipliers under specified business rules.

    Coding & AlgorithmsTechnical Screen
  • DoorDashHardSoftware Engineer
    Calculate Daily Driver Pay

    This question evaluates event-driven time-interval processing, interval-overlap arithmetic, rate computation, and robustness to malformed, duplicate, or unordered events when aggregating a driver's pay from a day's log.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Calculate Driver Payments

    Implement a payout calculation system for delivery drivers by deduplicating order logs, merging overlapping active-time intervals, and computing base pay, delivery bonuses, and tips.

    Coding & AlgorithmsOnsiteintervalssortinghash-table
  • DoorDashEasySoftware Engineer
    Compute Courier Delivery Pay

    This question tests the ability to handle time intervals and calculate cumulative earnings based on overlapping delivery pay rates.

    Coding & AlgorithmsTechnical ScreenArraysIntervalsGreedy
  • DoorDashMediumSoftware Engineer
    Compute Differences Between Catalog Trees

    This question evaluates proficiency in tree algorithms and hierarchical data comparison, including simultaneous traversal, subtree sizing, key-based node identity, and time/space complexity reasoning, and is commonly asked to assess algorithmic problem-solving and trade-off analysis when comparing structured datasets.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Compute Driver Pay with Double-Pay Windows

    This question evaluates a candidate's ability to perform interval arithmetic and aggregation for time-based pay computations, including handling overlapping intervals, half-open boundaries, capped double-pay application, and special-case handling for canceled orders.

    Coding & AlgorithmsTechnical Screen
  • DoorDashEasySoftware Engineer
    Compute Nearest Destination Distances

    This problem tests your ability to use Multi-Source Breadth-First Search (BFS) to find the distance from every empty cell to the nearest destination in a grid.

    Coding & AlgorithmsTechnical ScreenBFSGraphsGrid
  • DoorDashMediumSoftware Engineer
    Compute cart total with best promotion

    This question evaluates numerical reasoning for monetary calculations, handling of multiple promotion types, precision and rounding considerations, and edge-case handling such as empty carts and clamping totals within the Coding & Algorithms domain.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Compute dasher pay with peak-hour query

    This question tests the ability to handle overlapping time intervals and perform weighted calculations based on time-based pay multipliers.

    Coding & AlgorithmsOnsiteAlgorithmsIntervalsData Processing
  • DoorDashMediumSoftware Engineer
    Compute delivery times on a grid

    This question evaluates understanding of graph traversal and shortest-path algorithms, grid-based pathfinding, and data structure selection for representing sparse or large grids within the Coding & Algorithms domain.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Compute earliest arrival in time-grid

    This question evaluates algorithmic problem-solving and pathfinding skills on grid-based graphs, focusing on modeling time-dependent traversal constraints and reasoning about efficient search and supporting data structures.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Compute nearest dashmart and busiest assignments

    Compute nearest dashmart and busiest assignments 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.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Compute nearest dashmart distances for queries

    This question evaluates a candidate's understanding of graph traversal and shortest-path computation on grids, spatial reasoning about obstacles and sources, and the ability to analyze algorithmic scalability and complexity when answering many queries.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Compute nearest-exit distances in a grid

    Compute nearest-exit distances in a grid 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.

    Coding & AlgorithmsOnsite
  • DoorDashHardSoftware Engineer
    Count changed nodes between two menu trees

    This problem tests recursive tree traversal and hierarchical diffing strategies to identify structural and content changes between two versions of a menu tree.

    Coding & AlgorithmsTechnical ScreenTreesRecursionHash Maps
  • DoorDashMediumSoftware Engineer
    Count changed nodes in N-ary trees

    This question evaluates understanding of N-ary tree data structures, structural comparison of hierarchical versions, and the ability to reason about time and space complexity when detecting added, deleted, value-changed, or reparented nodes.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Debug a driver assignment bug

    This question evaluates debugging, root-cause analysis, unit/integration test design, observability, and system-resilience competencies within the Coding & Algorithms domain, emphasizing practical skills in reproducing failures, isolating defects, and implementing targeted fixes.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Debug and refactor a legacy module

    This question evaluates debugging, refactoring, naming and exception handling, input validation, code structure, and concurrency-safety design skills within a legacy codebase, requiring both hands-on code changes and higher-level reasoning about immutability, confinement, synchronization, and concurrent data structures.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Debug round-robin, DashMap, and simple cache

    This question evaluates skills in concurrent programming and stateful selection logic (round-robin load balancing), data structure invariants and debugging (custom hash map hashing vs equality, collision resolution, resizing and iterator correctness), simple in-memory caching strategies with TTL or size-based eviction, and unit test design.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Debug using logs and allocate tasks

    This question evaluates a candidate's skill in log-driven debugging, production incident investigation, and cross-functional task allocation, covering competencies such as structured and contextual logging, correlation identifiers, noise reduction, minimal reproducibility, feature-flagged isolation, triage coordination, hypothesis tracking, root-cause confirmation, regression prevention, and blameless postmortems. It is commonly asked to assess operational troubleshooting and teamwork under production uncertainty within the Coding & Algorithms category, testing practical application of debugging techniques alongside conceptual understanding of incident management and process-level coordination.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Design a hierarchical path registry

    Design a hierarchical path registry 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.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Design a single-machine LRU cache

    This question evaluates a candidate's ability to design an efficient in-memory LRU cache and apply concurrency control, covering eviction semantics, capacity management, key updates, and synchronization for thread safety.

    Coding & AlgorithmsTechnical Screen
  • DoorDashMediumSoftware Engineer
    Design dasher-to-order assignment algorithm

    This question evaluates a candidate's skills in real-time algorithm design and systems thinking for dynamic matching and optimization, including scalability, time/space complexity analysis, and handling partial or delayed information.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Design dynamic connectivity with alive nodes

    This question evaluates understanding of dynamic graph data structures, connectivity algorithms, state management for node activation/deactivation, complexity analysis, and concurrent operation considerations.

    Coding & AlgorithmsOnsite
  • DoorDashMediumSoftware Engineer
    Design hierarchical path store with create/set/get/remove

    This question evaluates a candidate's competency in hierarchical data structures, path parsing, API semantics, error signaling, complexity analysis, and unit testing for implementing a UNIX-style key-value path store.

    Coding & AlgorithmsTechnical Screen