Coding & Algorithms interview questions

Showing 1711–1740 of 3276 results

• Implement sparse vector dot productMedium

  Meta's sparse vector dot product question asks you to design a SparseVector class that stores only non-zero entries and computes dot products in time proportional to the number of non-zeros rather than the full vector length. It tests sparse data representation, two-pointer vs. hash-map trade-offs, and time/space complexity analysis.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Implement string dedup and mirror tree traversalMedium

  This question evaluates string-processing and tree-traversal algorithm skills, focusing on efficient group-deletion and streaming-capable string dedup operations and a mirrored boundary traversal of binary trees, and it tests algorithmic design, complexity guarantees, and correctness/termination reasoning.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Implement string sum and weighted city pickerMedium

  Implement string sum and weighted city picker 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 Screen
• Implement tree column grouping and minimal parentheses fixesMedium

  This question evaluates proficiency in tree and string algorithms, specifically binary tree traversal and coordinate-based column grouping with ordering/tie-breaking semantics, as well as string processing for minimal-parentheses deletion, and probes competence with data structures, streaming/online processing, correctness guarantees, and in-place space management. It is commonly asked in the Coding & Algorithms domain to assess algorithmic reasoning, implementation-level trade-offs and complexity analysis, testing both conceptual understanding of ordering and correctness and practical application skills such as achieving linear-time and space-efficient solutions and scaling to large inputs.

  MetaSoftware EngineerCoding & AlgorithmsOnline Assessment
• Implement weighted random index pickerMedium

  Implement weighted random index picker 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 & AlgorithmsOnsite
• Implement weighted random sampling with preprocessingMedium

  This problem tests your ability to optimize weighted random selection using binary search on prefix sums, balancing preprocessing time against query latency.

  MetaMachine Learning EngineerCoding & AlgorithmsOnsite
• Infer an Unknown Alphabet OrderMedium

  This question evaluates a candidate's competency in graph-based reasoning, inference of ordering constraints from sequences of strings, and algorithmic manipulation of characters and relations.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Longest Balanced Substring in a String of ParenthesesMedium

  A Meta coding interview problem: given a string made only of opening and closing parentheses, return the length of the longest contiguous substring that is correctly balanced. It tests careful handling of matched pairs, unmatched characters that break a run, and efficient processing of long inputs.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Map Random Tickets to Population-Weighted CitiesMedium

  Map deterministic tickets to cities in proportion to their population weights by building cumulative ranges and locating each possibly repeated ticket efficiently.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Maximize Letters from Disjoint WordsMedium

  This problem tests your ability to use recursion with backtracking and bit manipulation to find the maximum number of unique characters that can be formed by a subset of mutually disjoint words.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Maximize Unique Characters from WordsMedium

  This question evaluates a candidate's ability to reason about combinatorial constraints and set disjointness while maximizing unique coverage, testing competencies in algorithm design, combinatorics, and constraint-based optimization.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Maximize number with one digit swapMedium

  Maximize number with one digit swap 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 & AlgorithmsOnsite
• Maximize one stock trade profitMedium

  This question evaluates algorithm design skills for single-pass array processing, streaming data handling, and time/space complexity analysis within the Coding & Algorithms domain.

  MetaMachine Learning EngineerCoding & AlgorithmsOnsite
• Maximize score in 15-sum card gameMedium

  This problem tests your ability to use memoized recursion or dynamic programming to explore state spaces in a combinatorial game where you must decide which cards to remove to maximize your total score.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Maximize unique characters from a word listMedium

  This problem tests your ability to use recursion with backtracking or bitmasking to find the optimal subset of strings that maximize the total count of unique characters.

  MetaMachine Learning EngineerCoding & AlgorithmsOnsite
• Merge Two Lists of Non-Overlapping IntervalsMedium

  This question evaluates a candidate's ability to merge two pre-sorted, non-overlapping interval lists into a single consolidated set, a core array and two-pointer/merging skill in coding interviews. It tests correct handling of edge cases like touching endpoints versus true gaps, assessing precision in interval logic and algorithmic reasoning under linear-time constraints.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Merge overlapping intervalsMedium

  This problem tests your ability to manipulate array-based data by sorting and performing linear sweeps to consolidate overlapping ranges.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Merge two interval lists into a unionMedium

  This question evaluates a candidate's ability to implement interval merging algorithms, reason about edge cases such as touching boundaries, empty inputs, and invalid intervals, and perform time and space complexity analysis.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Minimum Round-Trip Flight CostMedium

  This question evaluates a candidate's ability to optimize over paired sequences using array traversal and running-minimum tracking, a core array-processing technique in coding interviews. It tests practical application of single-pass optimization under an ordering constraint rather than brute-force pairwise comparison, commonly used to assess algorithmic efficiency and edge-case handling.

  MetaSoftware EngineerCoding & AlgorithmsOnsite
• Navigate unknown grid to locate targetMedium

  This question evaluates algorithmic problem-solving and spatial reasoning skills, particularly graph traversal, exploration in unknown environments, state encoding for relative coordinates, and reasoning about correctness.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Optimize Oculus Data Streaming with Bandwidth ConstraintsMedium

  This question evaluates a candidate's ability in algorithm design and problem decomposition for array segmentation and interval coverage, focusing on reasoning about cumulative constraints for streaming data and geometric interval intersections.

  MetaData ScientistCoding & AlgorithmsOnsite
• Optimize Travel Costs and Generate Rotational Symmetric NumbersMedium

  This question evaluates algorithmic optimization and complexity-analysis skills by combining array-based time-dependent pricing for round-trip cost minimization with combinatorial generation of rotationally symmetric (strobogrammatic) k-digit numbers.

  MetaData ScientistCoding & AlgorithmsTechnical Screen
• Optimize a Fifteen-Sum Card StrategyHard

  This problem tests your ability to optimize a combinatorial search space through memoization and dynamic programming to determine the maximum win rate of a card-based strategy.

  MetaMachine Learning EngineerCoding & AlgorithmsOnsite
• Optimize flight costs and find grid pathMedium

  This question evaluates algorithm design and problem-solving skills for array-based cost optimization and grid pathfinding, including selection under ordering constraints, path existence detection and path reconstruction, together with correctness and edge-case reasoning.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Optimize repeated-value vectors and compute exclusive timesMedium

  This question evaluates proficiency in data-structure and algorithmic concepts such as run-length encoding for compressed vectors and interval/nesting reasoning for computing exclusive execution times.

  MetaMachine Learning EngineerCoding & AlgorithmsTechnical Screen
• Optimize ribbon piece length by binary searchMedium

  This question evaluates understanding of binary-search-on-answer techniques and monotonic predicates, complexity analysis, and implementation-level handling of integer overflow and extreme edge cases in numeric partitioning, situated in the coding and algorithms domain and emphasizing practical implementation considerations rather than purely theoretical proofs. It is commonly asked because it reveals whether an interviewee can reason about monotonicity and design an O(n log max(lengths)) solution that remains robust under very large k, large element values, and potential integer overflow.

  MetaMachine Learning EngineerCoding & AlgorithmsOnsite
• Palindrome After Deleting at Most One CharacterMedium

  This problem tests your ability to optimize string traversal using a two-pointer approach, specifically handling conditional branch logic when an inconsistency is detected.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen
• Produce asymmetric side views of a binary treeMedium

  Produce asymmetric side views of a binary tree 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 Screen
• Read Current and Historical Field Values with ExpirationMedium

  Design an in-memory key-field-value store that supports historical queries, time-to-live (TTL) expiration, and field deletions without corrupting past states.

  MetaMachine Learning EngineerCoding & AlgorithmsOnline Assessment
• Remove minimum invalid mixed bracketsHard

  This Coding & Algorithms problem evaluates string-processing and bracket-matching skills, specifically understanding of stack-based parsing, handling multiple bracket types, and minimizing removals while preserving non-bracket characters.

  MetaSoftware EngineerCoding & AlgorithmsTechnical Screen