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 1411–1440 of 3276 results
This question evaluates a candidate's ability to design and implement time-ordered in-memory data structures and APIs, testing competencies in temporal event ordering and precedence, scheduled deletions, priority-sorted retrieval, user-task assignment, and historical (time-travel) queries.
InstacartSoftware EngineerCoding & AlgorithmsOnline AssessmentThis problem tests your ability to manage overlapping time intervals, perform efficient lookups on historical state changes, and calculate cumulative payroll based on dynamic shift rates.
InstacartSoftware EngineerCoding & AlgorithmsOnline AssessmentThis interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Optimize file reading and expression DFS states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
InstacartSoftware EngineerCoding & AlgorithmsHR ScreenThis question evaluates proficiency in on-disk file I/O, streaming algorithms, offline indexing for sublinear lookups, and system-level performance considerations for validating credentials in large files.
InstacartSoftware EngineerCoding & AlgorithmsHR ScreenThis question evaluates proficiency in grid traversal, sequence-driven state tracking, string manipulation, and boundary/obstacle validation while requiring time and space complexity reasoning.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates file parsing, matrix indexing with a specified coordinate origin, handling multiple indexed blocks, and string assembly into an ordered password, testing competencies in file I/O, coordinate transformations, and robust input handling.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteThis interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Pivot order-status counts states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteResolve a target variable through an acyclic chain of named assignments until reaching an integer literal, independent of definition order.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteThis problem tests your ability to efficiently merge and find elements in sorted arrays, focusing on optimal time complexity and edge case handling.
InstacartMachine 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 Solve bank, password, expression algorithm tasks states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates a candidate's ability in parsing, expression evaluation, and nested string decoding, including handling malformed input, character encoding nuances, and large-file streaming considerations.
InstacartSoftware EngineerCoding & AlgorithmsOnsiteThis problem tests the ability to iterate through sorted intervals and calculate values based on overlapping ranges, requiring careful boundary handling.
Interactive BrokersSoftware EngineerCoding & AlgorithmsOnline AssessmentPractice a Interactive Brokers coding interview problem focused on calculate tax in a progressive marginal tax system. The prompt emphasizes edge cases, clean implementation, and verifiable test behavior without revealing the solution.
Interactive BrokersSoftware EngineerCoding & AlgorithmsOnline AssessmentA data engineering coding screen on greedy scheduling under a cooldown constraint: produce an ordered list of products, one per day, where each product type must cool down for `space` days before it can be produced again. Candidates must return the minimum number of days, ideally in O(n) time using a hash map of last-produced days.
Interactive BrokersData EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates string manipulation and algorithmic problem-solving skills, focusing on identifying palindromic substrings and reasoning about performance and edge cases. Commonly asked in the Coding & Algorithms domain to assess practical algorithmic application, it gauges understanding of time/space complexity, input constraints, and robustness in implementation.
IntersystemsSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests creative logical reasoning and the ability to decompose time-based tasks into parallelizable components without standard measurement tools.
IntersystemsSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your understanding of ordered map iteration, the impact of modifying collection traversal, and handling accumulation logic in a state-dependent loop.
IntersystemsSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to handle array-based arithmetic and carry-over logic, specifically focusing on edge cases like digit overflow and resizing the array.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of graph traversal and shortest-path computation, including modeling business relationships as undirected graphs and interpreting degrees of separation on the shortest path.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates proficiency in text parsing, tokenization, and numeric comparison applied to command-line style output, emphasizing robust handling of varied input formats and edge cases.
IntuitSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates understanding of cache eviction policies (LRU and LFU), frequency tracking, and the design of data structures that support efficient get/put operations while meeting time and space complexity constraints.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to perform manual addition on an array representing a large integer, specifically handling carry propagation and dynamic resizing when the integer overflows its current digit count.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to reconstruct a valid topological ordering (parent-before-child) from a parent-child relationship array while maintaining lexicographical minimality.
IntuitSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates competencies in string algorithms (word segmentation and palindrome validation), data structures and complexity analysis, and practical frontend React implementation with performance considerations.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of string algorithms, combinatorial counting, and algorithmic optimization for aggregating pairwise mismatch costs across all substrings.
IntuitSoftware EngineerCoding & AlgorithmsOnline AssessmentThis question evaluates understanding of bracket matching and string parsing, testing competency with basic data structures and algorithmic reasoning such as stack-based matching and correct handling of nested delimiters.
IntuitSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates scheduling and ordering under timing constraints, read-after-write hazards, intra-batch dependency handling, and the ability to parse and execute register read/write operations.
IxanaSoftware EngineerCoding & AlgorithmsTechnical ScreenThis problem tests your ability to detect cycles in a directed graph to determine if a set of dependent tasks can be successfully completed.
J.P. MorganSoftware EngineerCoding & AlgorithmsTechnical ScreenThis question evaluates understanding of dynamic programming for strings, specifically longest palindromic subsequence concepts such as memoization, bottom-up DP, space optimization and subsequence reconstruction.
J.P. MorganSoftware EngineerCoding & AlgorithmsOnsiteThis question evaluates algorithmic problem-solving across arrays and strings, covering concepts such as sliding-window techniques on circular arrays, wraparound handling, index recovery after single-character deletion, duplicate-character considerations, and time/space complexity analysis within the Coding & Algorithms domain.
J.P. MorganSoftware EngineerCoding & AlgorithmsTechnical Screen