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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.
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Showing 541–570 of 1706 results
- GleanMediumMachine Learning EngineerDetermine Reachability in Train Schedule
Solve train-schedule reachability with waiting and transfers using time-respecting graph search. The answer models earliest station arrival, preprocesses station visits, handles forward-only train routes, and explains transfer edge cases and complexity.
Coding & AlgorithmsTechnical Screen - GleanMediumSoftware EngineerFind the Kth Largest in Two Sorted Arrays
This question evaluates proficiency with array manipulation and selection algorithms, specifically understanding order statistics and working with two sorted sequences.
Coding & AlgorithmsTechnical Screen - GleanMediumSoftware EngineerImplement 2048 Game Logic
This question evaluates array and matrix manipulation, stateful simulation of game mechanics, and handling edge cases such as merge constraints, single-merge-per-move rules, and empty-cell management.
Coding & AlgorithmsTechnical Screen - GleanHardSoftware EngineerImplement 2048 tilt move
This question evaluates a candidate's ability to implement array and matrix manipulation, deterministic state-transition logic, and rule-based merging behavior in a grid-based simulation.
Coding & AlgorithmsTechnical Screen - GleanMediumSoftware EngineerImplement a Byte Pair Encoding (BPE) Tokenizer
Implement a Byte Pair Encoding (BPE) tokenizer with training, encoding, and decoding capabilities using frequency-based iterative merging.
Coding & AlgorithmsTechnical ScreenNLPStringsDesign - GleanMediumSoftware EngineerRestore an Array with One Displaced Element
Restore a nearly sorted array where at most one element has been removed and reinserted elsewhere, in linear time and without mutating the input array.
Coding & AlgorithmsTechnical Screenarraystwo-pointerssorting - GleanMediumSoftware EngineerReturn Top Department Suggestions
Design an in-memory prefix search system that returns the top-k department suggestions based on popularity scores, with deterministic tie-breaking.
Coding & AlgorithmsTechnical ScreenTrieHeapPrefix Search - GleanHardSoftware EngineerSearch Words in a Character Grid
This question evaluates algorithmic problem-solving in grid traversal and multi-word string search, targeting competencies in pathfinding, string matching, efficient use of data structures for shared prefixes, and time/space complexity analysis within the Coding & Algorithms domain.
Coding & AlgorithmsTechnical Screen - GleanHardSoftware EngineerSimulate document assignment to indexers
This question evaluates simulation of parallel worker scheduling, time-based queue processing, modular assignment logic, and aggregation/ranking (top-k and percentage) competencies for tracking per-worker workloads.
Coding & AlgorithmsTechnical Screen - Goldman SachsMediumSoftware EngineerDesign a Workspace Resource Manager
This problem tests your ability to design a tree-based hierarchical resource management system and implement efficient operations for path-based access, relocation, and cycle detection.
Coding & AlgorithmsTechnical ScreenTreesGraphsData Structures - Goldman SachsMediumSoftware EngineerFind the Root of the Largest Tree in a Child-to-Parent Forest
Given a list of child-to-parent pairs that form a forest of rooted trees, return the root ID of the tree with the most nodes, breaking size ties by the smallest root ID. Tests building a forest from an edge list, identifying roots, counting tree sizes, and applying a precise tie-break rule.
Coding & AlgorithmsTechnical Screen - Goldman SachsEasySoftware EngineerImplement a String Deque
This question evaluates competence with fundamental data structures and algorithms by requiring an implementation of a string double-ended queue (deque), checking understanding of constant-time (O(1)) operations, manipulation of node links or references, and correct handling of edge cases; category: Coding & Algorithms; level: practical implementation rather than purely conceptual. It is commonly asked to assess the ability to implement low-level data structure mechanics, guarantee performance bounds, and expose attention to correctness and boundary conditions in algorithmic coding tasks.
Coding & AlgorithmsTechnical Screen - Goldman SachsMediumQuantitative ResearcherMinimum-Cost Round Trip Visiting Every City Once with Asymmetric Costs
Given a complete matrix of possibly asymmetric travel costs between up to 16 cities, return the minimum cost of a round trip that starts at city 0, visits every other city exactly once and returns to city 0. The problem tests exact optimization over subsets of cities within tight limits.
Coding & AlgorithmsTechnical Screen - Goldman SachsMediumSoftware EngineerSolve string and hashmap coding tasks
This problem tests your ability to manipulate strings, utilize hash maps for grouping data, and perform iterative simulations based on sequential command logs.
Coding & AlgorithmsTechnical ScreenStringsHashMapsData-Processing - Goldman SachsMediumSoftware EngineerSolve string and hashmap interview tasks
This question evaluates proficiency in string manipulation and hash-based aggregation, specifically skills such as frequency counting, map/dictionary usage, and numeric aggregation for averages.
Coding & AlgorithmsTechnical Screen - Goldman SachsMediumQuantitative ResearcherTotal Rainwater Trapped Above an Elevation Profile of Unit-Width Bars
Given the heights of adjacent unit-width bars in an elevation profile, compute the total amount of rainwater that stays trapped between them after rain, with water spilling off both open ends. The coding problem tests reasoning about the bars that bound each position and handling up to 100,000 bars efficiently.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerAdd two big integers from digit lists
This question evaluates algorithmic skills in manipulating linked lists or arrays to perform addition of large integers, focusing on carry propagation, handling differing lengths, and analysis of time and space complexity.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerAnswer parity-alternation range queries
This problem tests your ability to use prefix sums or dynamic tracking to determine if a range [L, R] consists of elements that alternate between odd and even parity in O(1) time after O(N) preprocessing.
Coding & AlgorithmsTechnical ScreenArraysPrefix SumAlgorithms - GoogleMediumSoftware EngineerBuild Prefix Lookup with a Trie
Tests implementation of a Trie (prefix tree) data structure to support word insertion, exact word search, prefix existence checks, and lexicographical autocomplete suggestions with a capacity limit.
Coding & AlgorithmsTechnical Screentriestringsdfs - GoogleMediumSoftware EngineerCan board states be transformed?
This problem tests your ability to determine if one board state can be transformed into another using reversible movement rules, requiring the identification of invariants to avoid exhaustive searching.
Coding & AlgorithmsTechnical ScreenStringsInvariantsTwo Pointers - GoogleMediumSoftware EngineerCheck Whether Digits Are Monotone Increasing
Determine if a non-negative integer has digits that are monotonically non-decreasing from left to right, handling edge cases without unnecessary memory allocation.
Coding & AlgorithmsTechnical Screenmathstringsfundamentals - GoogleEasySoftware EngineerCheck an Interval Against Existing Intervals for Conflicts
Determine whether a proposed half-open interval overlaps with any interval in an unsorted list. This tests basic interval overlap logic and boundary condition handling.
Coding & AlgorithmsTechnical ScreenIntervalsArraysGeometry - GoogleMediumSoftware EngineerCheck if all substrings are anagrams of words
This question evaluates string-processing skills and combinatorial reasoning about character multisets, specifically anagram recognition, substring enumeration, and the use of efficient representations for repeated checks.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerCheck if all substrings are dictionary words
This question evaluates string-processing skills such as substring enumeration and membership testing against a dictionary, along with algorithmic reasoning about correctness and complexity.
Coding & AlgorithmsTechnical Screen - GoogleMediumSoftware EngineerChoose optimal guesses for green-only Wordle
This problem tests your ability to model uncertainty and implement a greedy strategy to minimize the expected search space size when provided with restricted (green-only) feedback.
Coding & AlgorithmsTechnical ScreenProbabilityGreedyOptimization - GoogleHardSoftware EngineerCompute Turnstile Crossing Times
This problem tests your ability to manage state in a queue-based simulation and implement complex tie-breaking logic using data structures like heaps or prioritized queues.
Coding & AlgorithmsTechnical ScreenSimulationQueueHeap - GoogleMediumSoftware EngineerCompute distance to nearest taxi in grid
This problem tests your ability to efficiently compute shortest path distances from multiple sources to all reachable grid cells using multi-source Breadth-First Search (BFS).
Coding & AlgorithmsTechnical ScreenBFSGraphGrid - GoogleHardSoftware EngineerCompute minimax grid path and network delay
This question tests the ability to solve pathfinding problems using non-standard cost metrics: first, finding a minimax path in a grid, and second, calculating the earliest arrival time in a network with weighted edges.
Coding & AlgorithmsTechnical ScreenDynamic ProgrammingDijkstraBinary Search - GoogleMediumSoftware EngineerCompute minimum servers for cyclic tasks
This problem tests your ability to manage overlapping intervals in a circular domain by converting cyclic tasks into linear sub-intervals and applying a sweep-line or greedy approach to determine resource requirements.
Coding & AlgorithmsTechnical ScreenIntervalsGreedySweep-line - GoogleMediumData ScientistCompute precision–recall curve on imbalanced data
This question evaluates a data scientist's competency in model evaluation for imbalanced binary classification, covering understanding of precision–recall dynamics, calibration, AUPRC, cost‑sensitive metrics, and practical implementation concerns like computing thresholds and handling ties and numerical edge cases; domain: Coding & Algorithms and machine learning model evaluation. It is commonly asked in technical interviews because it assesses both conceptual understanding of evaluation trade‑offs and the practical application of efficient, robust metric computation and threshold selection under asymmetric costs and operational constraints.
Coding & AlgorithmsTechnical Screen
Glean
Goldman Sachs
Google