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 1651–1680 of 3276 results
Determine whether an integer array containing negative values has any nonempty contiguous subarray that equals a target, using prefix sums for a linear-time solution.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to manipulate string structures using stack-based logic and perform graph-based dependency resolution using topological sort.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates a candidate's ability to reason about contiguous subarray sums, efficient array manipulation, and handling large numeric ranges within algorithmic constraints, and it falls under the Coding & Algorithms domain as a practical algorithmic implementation problem.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenEvaluate arithmetic expression without parentheses 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.
MetaSoftware EngineerCoding & AlgorithmsOnsiteEvaluate expression without stack, constant space 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.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to adapt Breadth-First Search (BFS) to a state-space where the current location is augmented by a collection of keys, effectively transforming the grid into a larger, multi-layered graph.
MetaSoftware EngineerCoding & AlgorithmsOnsite- Extend a Maze SolverMedium
This question evaluates algorithmic problem-solving and software engineering skills, specifically graph traversal (BFS), state-space modeling for keys and doors, handling movement constraints, and debugging an existing codebase within the Coding & Algorithms domain.
MetaSoftware EngineerCoding & AlgorithmsTechnical Screen This question evaluates understanding of data structures and algorithms for stateful resource management, covering bookkeeping of per-user quotas, file metadata operations (copy, compress/decompress), string filtering and sorting, and efficient selection and deletion of largest elements.
MetaSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates grid-based graph traversal and algorithmic problem-solving skills, including concepts such as multi-source breadth-first search, handling sentinel values, and performing in-place updates.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenA binary tree coding problem: given a tree with distinct values, a target node and a distance k, return every node exactly k edges away, including nodes reached by moving up through ancestors. It tests traversal in both directions of a tree, level-order input parsing and careful handling of visited nodes.
MetaSoftware EngineerCoding & AlgorithmsOnsiteFind the index of any strict local minimum in a nonempty array whose adjacent values differ, using an iterative logarithmic-time algorithm. The task tests search invariants, boundary-as-infinity semantics, singleton and monotone arrays, and correctness when several indices are valid.
MetaSoftware EngineerCoding & AlgorithmsOnsiteThis pair of problems evaluates array manipulation and algorithmic problem-solving skills, specifically order-statistics for selecting the k-th largest element and maximizing consecutive sequences under constrained transformations for the vacation streak problem.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates algorithmic problem-solving and data-structure competencies, focusing on selection algorithms and time/space complexity reasoning for the k-th largest element and tree traversal, lowest common ancestor discovery with attention to BST properties, parent pointers, and external-memory constraints.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to use bitmasking and backtracking with pruning to solve a variation of the maximum set packing problem under character constraints.
MetaMachine Learning EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to efficiently manage and query prefix-based string sets using a Trie (prefix tree) data structure.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to efficiently identify all words in a list that contain at least one other word from the same list as a substring, utilizing optimized string processing or data structures like Tries.
MetaMachine Learning EngineerCoding & AlgorithmsOnsiteThis problem tests the ability to adapt binary search to identify a local minimum in an unsorted array, focusing on handling boundary conditions and non-strict inequality logic.
MetaSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates proficiency in string algorithms, substring search techniques, and algorithmic complexity analysis within the Coding & Algorithms domain.
MetaMachine Learning EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates array and tree algorithm skills, testing competency in identifying longest balanced subarrays in binary sequences and locating maximal strictly increasing downward paths in binary trees.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates a candidate's ability to reason about interval overlap counting, manage range endpoints efficiently, and balance time-space trade-offs when identifying points that maximize coverage.
MetaSoftware EngineerCoding & AlgorithmsOnsiteFind k most frequent elements, discuss O(n) 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.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenA classic Meta software engineer onsite coding question: return the k-th largest element from an unsorted integer array, handling duplicates correctly. It tests order statistics and selection algorithms — sort, size-k min-heap (O(n log k)), and quickselect (O(n) average) — and the candidate's ability to beat a full sort.
MetaSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates algorithmic problem-solving and data-structure knowledge, focusing on selection in a row-and-column-sorted matrix and the comparative use of min-heaps versus value-space binary search along with time/space complexity and edge-case analysis.
MetaMachine Learning EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to optimize string processing algorithms, specifically moving from a brute-force approach to an efficient expansion-based technique for identifying palindromic patterns.
MetaMachine Learning EngineerCoding & AlgorithmsOnsiteFind minimum and most frequent number efficiently 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.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates a candidate's proficiency in array traversal, interval reasoning, handling edge cases including empty inputs and 32-bit integer boundary conditions, and enforcing time and space complexity constraints.
MetaSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates algorithm design and analysis skills—particularly time–space tradeoffs, frequency counting techniques (sorting, hashing, and counting arrays), and handling streaming or memory-constrained inputs in the Coding & Algorithms domain.
MetaSoftware 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 Find power-of-two subarrays within sum range states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
MetaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates proficiency with array algorithms and range-query reasoning, testing understanding of max/min behavior over contiguous subarrays and use of appropriate data-structure techniques; it belongs to the Coding & Algorithms domain.
MetaSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates proficiency in string processing, handling character-uniqueness constraints, and algorithmic thinking about time and space efficiency.
MetaSoftware EngineerCoding & AlgorithmsOnsite