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 361–390 of 3276 results
This question evaluates the ability to interpret time-ordered profiler event logs, compute inclusive and exclusive function runtimes, reason about call-stack semantics, and recognize anomalies such as recursion, cycles, missing end events, or non-returning functions.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteSimulate a virtual machine's instruction set, detect an infinite loop cycle, and find the single instruction modification (between jmp and nop) that allows the program to terminate normally.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenGenerate function start and end events from timestamped stack samples, including independently debounced frames across consecutive samples. Address transient appearances and absences, changing stack suffixes, shared timestamps, deep stacks, end-of-input behavior, complexity, and online processing.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates algorithmic and systems engineering skills related to batch image processing, parallelization, I/O versus CPU trade-offs, and deterministic output association within the Coding & Algorithms domain.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates competency in concurrent and parallel processing, practical image manipulation with Python libraries (Pillow), resource management for memory and file I/O, robust error handling, and performance measurement.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to design a decorator that memoizes function results using an LRU policy while ensuring the cache survives process restarts via disk serialization.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates a candidate's ability to design and implement an LRU cache in Python that supports variable-length positional and keyword arguments with canonical, deterministic hashing for semantically equivalent calls and O(1) get/put via a hash map plus a doubly linked list; it falls under the Coding & Algorithms domain and primarily tests practical implementation skills, API robustness, hashing/equality subtleties, and algorithmic complexity guarantees. The persistence follow-up evaluates understanding of serialization and storage design — on-disk formats, versioning, and atomic write strategies — and compares trade-offs between binary pickle and JSON-based serialization in terms of security, compatibility, and performance, reflecting both conceptual design and practical system-level considerations.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates a candidate's ability to implement an LRU caching mechanism in Python, including decorator design, argument canonicalization for positional args, *args, and **kwargs, handling unhashable inputs, eviction semantics, cache metadata operations (clear, cache_info), and JSON-based persistence and versioning.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to design an in-memory task management system with concurrency-aware state tracking and implement an efficient file-deduplication routine using hashing.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates skills in designing and implementing a stateful in-memory banking system, covering account modeling, transfer lifecycle and expiration handling, balance management, and tracking aggregate outgoing amounts.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteDesign and implement an in-memory image transformation engine that applies sequential operations (grayscale, brightness scaling, nearest-neighbor resizing) over a batch of images efficiently.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates a candidate's ability to design and implement an efficient in-memory cache with eviction behavior, testing understanding of data structure selection, state management, and time/space complexity under capacity constraints.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteDesign and implement a greedy longest-match text tokenizer that validates vocabulary, supports configurable unknown-token coalescing, and emits token IDs alongside their exact substring matches.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteDesign and implement a concurrent batch image processor that executes a sequence of matrix transforms across worker threads or processes while isolating per-job failures.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenImplement an in-memory DNS resolver supporting A and CNAME record lookups, domain name normalization, TTL expiration, and CNAME alias chain cycle detection.
AnthropicMachine Learning EngineerCoding & AlgorithmsOnline AssessmentDesign an in-memory task manager supporting per-user task versioning, time-to-live (TTL) expiration, and point-in-time historical queries.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to design a hierarchical file system data structure and implement operations for directory traversal, file manipulation, and path normalization.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to design a multi-threaded web crawler that efficiently traverses a site while respecting domain constraints and avoiding redundant work.
AnthropicMachine Learning EngineerCoding & AlgorithmsOnsiteThis question evaluates the ability to design and implement an extensible prefix tree (trie), covering competencies in Unicode-aware string handling, memory and time optimization, concurrency or thread-safety considerations, and support for operations like insert, search, startsWith, countPrefix and erase.
AnthropicMachine Learning EngineerCoding & AlgorithmsOnsiteImplement an in-memory nested key-value store supporting field-level time-to-live (TTL) expiration and snapshot backup/restore operations.
AnthropicSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates a candidate's competence in data structures and algorithms for time-ordered state tracking, time-series indexing, conflict resolution (last-write-wins), memory-efficient storage, and concurrent system behavior under high update rates.
AnthropicMachine 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 Implement crawler, dedup, and persistent LRU states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteImplement streaming file deduplication that filters by size, fingerprint and hash, then compares bytes to rule out hash collisions. It covers large-file chunking, batched disk I/O, parallelizing across cores or machines, a dry-run report, and hard links that never cross devices. Follow-ups turn it into a command-line tool that handles symbolic links, unreadable files, error cases, and options to move or delete duplicates.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates skills in graph traversal and cycle detection, hostname-based filtering, URL parsing, and basic network error handling. Commonly asked in Coding & Algorithms interviews, it assesses algorithmic reasoning about traversal strategy and complexity (time and space) analysis while balancing conceptual understanding with practical implementation details.
AnthropicSoftware EngineerCoding & AlgorithmsTechnical ScreenThis set of problems evaluates implementation correctness and attention to formatting for a staircase-printing routine alongside distributed-algorithms reasoning for computing a global mode/median, testing algorithmic thinking, I/O handling, synchronization, and communication-cost trade-offs in the Coding & Algorithms domain.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates competency in concurrent programming, synchronization primitives, and implementation of thread-safe bounded blocking queues within the Coding & Algorithms domain.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteDesign an in-memory key-value store supporting nested transactions with begin, commit, rollback, get, set, and delete operations.
AnthropicSoftware EngineerCoding & AlgorithmsOnsite- LRU CacheMedium
This question tests the ability to combine a hash map and a doubly linked list to implement an LRU cache with O(1) performance for both get and put operations.
AnthropicSoftware EngineerCoding & AlgorithmsOnsite Implement a filesystem path resolution function that normalizes paths containing '.', '..', and symbolic links while detecting cycles.
AnthropicSoftware EngineerCoding & AlgorithmsOnsiteImplement a breadth-first search crawler that traverses pages starting from a seed URL, filtering for pages sharing the same domain and properly deduplicating visited URLs.
AnthropicSoftware EngineerCoding & AlgorithmsOnsite