Topic
Coding & Algorithms interview questions
3276 Coding & Algorithms questions from 366 companies, with hints, runnable code and solution walkthroughs.
273 easy2539 medium464 hard
Coding & Algorithms interview questions by the numbers
Last updated
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
Most mentioned in interview experiences
- 1.Solve Algorithmic Challenges in Online Coding Assessments15 reports
- 2.Solve LeetCode string and list problems11 reports
- 3.Solve sliding-window and heap problems8 reports
- 4.Implement LRU cache with O(1) ops7 reports
- 5.Implement and Analyze an LRU Query Cache6 reports
- 6.Determine Length of Longest Unique Substring5 reports
- 7.Match-3 Grid: Find Horizontal and Vertical Runs, Then Clear and Drop Cells5 reports
- 8.Design a single- and multi-threaded web crawler4 reports
- 9.Find an Exit in a URL Maze4 reports
- 10.Find deployable slots in a recurring week from allowed and freeze windows4 reports
Counted from 781 candidate interview experiences on Katkat. How we collect and count
Showing 2821–2850 of 3276 results
This question evaluates understanding of kinematics, motion modeling, and numerical reasoning for safety-critical control logic, focusing on stopping-distance computation and the impact of reaction time on braking decisions.
TeslaMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates algorithmic problem-solving with arrays and analysis of time-space trade-offs in the Coding & Algorithms domain, and is commonly asked to assess a candidate's ability to transform brute-force approaches into efficient linear-time solutions while reasoning about memory usage.
TeslaSoftware EngineerCoding & AlgorithmsTechnical ScreenTests matrix traversal techniques, specifically using DFS/BFS to identify connected components and multi-source BFS to find the shortest path between them.
TeslaSoftware EngineerCoding & AlgorithmsOnsiteThis multi-part question evaluates algorithmic problem-solving and data-structure competency, covering expression parsing, array and sequence manipulation, sorting-based counting, interval merging, graph traversal/union-find, in-place rearrangement, hashing for set operations, and DAG/topological ordering within the Coding & Algorithms domain.
TeslaSoftware EngineerCoding & AlgorithmsHR ScreenThis question tests the ability to handle window functions for running totals and conditional aggregation to transform raw manufacturing logs into formatted monthly production reports.
TeslaData EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to manage state and look-ahead logic when processing a sequence of events (bowling rolls) governed by specific conditional scoring rules.
The Trade DeskSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates a candidate's ability to implement an in-memory cloud storage system, exercising skills in data structures and stateful API design, string handling and pattern matching, sorting and eviction algorithms, and per-user resource accounting.
The Trade DeskSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates proficiency with piecewise-linear interpolation on strictly increasing (monotonic) arrays, sound handling of out-of-range queries (error, clamp, extrapolate, or None/NaN), and efficient interval search over sorted data with a target of O(log n). It also probes real-world judgment about when each out-of-range policy is appropriate and which non-bisect strategies exist.
The Trade DeskData ScientistCoding & AlgorithmsTechnical ScreenThis question tests practical coding ability in probabilistic simulation, requiring implementation of a Monte Carlo method to estimate conditional win probabilities under two decision strategies. It assesses a data scientist's skill in translating a classic probability scenario into working randomized code rather than relying on closed-form analysis.
ThumbtackData ScientistCoding & AlgorithmsTechnical ScreenThis question evaluates implementation skills in basic descriptive statistics (min, mean, median), numerical stability in online aggregation methods, robust handling of edge cases like None/NaN and extreme numeric ranges, and algorithmic complexity reasoning in the Coding & Algorithms domain for a Data Scientist role.
ThumbtackData ScientistCoding & AlgorithmsOnsiteThis question evaluates understanding of graph search algorithms, heuristic properties (admissibility and consistency), path optimality and time/space complexity, requiring application of BFS, uniform-cost search, A*, and DFS on a concrete weighted graph.
TikTokData ScientistCoding & AlgorithmsTechnical ScreenThis question evaluates data manipulation and aggregation skills, focusing on handling duplicate values within collections and computing numerical summaries of list data.
TikTokData ScientistCoding & AlgorithmsOnsiteCompute city skyline silhouette 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.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of subsequences, dynamic programming and algorithmic optimization for array processing, and is categorized under Coding & Algorithms; it emphasizes practical application of algorithm design and complexity analysis rather than purely theoretical knowledge.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to optimize path calculations in a non-linear data structure using dynamic programming, specifically focusing on space complexity optimization.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of graph algorithms and dependency resolution, specifically topological sorting and cycle detection, along with competence in choosing appropriate data structures and analyzing time/space complexity.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates proficiency with array manipulation, parity-aware summation, and combinatorial counting when elements are removed, situating it in the Coding & Algorithms domain.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests grid traversal (DFS/BFS) and the ability to represent spatial structures in a canonical form to identify unique patterns.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates skills in graph and grid algorithms, topology-aware adjacency (torus wrap-around), and maintaining dynamic connectivity under incremental updates.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to optimize subarray sum calculations from an O(n^2) approach to O(n) using a hash map for prefix sum tracking.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates proficiency in mutable data structure operations, specifically linked list node removal and binary tree node replacement/deletion, requiring knowledge of traversal, pointer/reference manipulation, and edge-case handling.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates a candidate's understanding of data structures and algorithm design, specifically skills in implementing constant-time cache operations, eviction policies, update handling, and concurrency/thread-safety considerations.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates dynamic programming, state-space reachability, and constrained transition reasoning, along with skills in hash-based memoization and time/space complexity analysis.
TikTokMachine Learning EngineerCoding & AlgorithmsOnsiteThis question evaluates a candidate's understanding of dynamic programming and string-processing skills, along with algorithmic complexity analysis for segmentation problems.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Differentiate virtual and pure virtual functions states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of Java framework internals and related competencies including dependency injection, aspect-oriented programming and proxy mechanisms, transaction management, annotation processing, bean lifecycle, classpath scanning, bean scopes, and circular dependency detection or resolution.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to model dependencies as a directed graph and determine a valid sequence using topological sorting (Kahn's algorithm or DFS).
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenFind and count target-sum subarrays 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.
TikTokMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates mastery of searching algorithms and algorithmic complexity analysis, particularly the ability to locate boundary positions within a sorted array.
TikTokSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates algorithmic problem-solving and data-structure reasoning, focusing on order statistics and operations on a row- and column-sorted matrix within the Coding & Algorithms domain.
TikTokSoftware EngineerCoding & AlgorithmsTechnical Screen