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Recommend movies by shared ratings

Last updated: Mar 29, 2026

Quick Overview

This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Recommend movies by shared ratings states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • Medium
  • Coinbase
  • Coding & Algorithms
  • Software Engineer

Recommend movies by shared ratings

Company: Coinbase

Role: Software Engineer

Category: Coding & Algorithms

Difficulty: Medium

Interview Round: Technical Screen

Write a function recommendations(user, ratings) that returns a list of movies to recommend to the given user based on shared preferences. Each rating is a triplet [User Name, Movie Name, Rating] where Rating ∈ {1,2,3,4,5} (strings). Define two users as having similar taste if they have both rated the same movie with a 4 or 5. Recommend a movie to the user if the user has not rated it and any similar-taste user rated it a 4 or 5. Ensure the output contains unique movie names and justify any ordering you choose.

Quick Answer: This interview question evaluates algorithm design, data structures, correctness, complexity, edge cases, and implementation details in a realistic interview setting. A strong answer for Recommend movies by shared ratings states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Solution

# Solution Alignment The prompt asks for an implementation-level answer. The safest way to present it is to define the state, maintain clear invariants, then walk through complexity and tests. ## Problem Restatement Write a function recommendations(user, ratings) that returns a list of movies to recommend to the given user based on shared preferences. Each rating is a triplet [User Name, Movie Name, Rating] where Rating ∈ {1,2,3,4,5} (strings). Define two users as having similar taste if they have both rated the same movie with a 4 or 5. Recommend a movie to the user if the user has not rated it and any similar-taste user rated it a 4 or 5. Ensure the output contains unique movie names and justify any ordering you choose. ## Recommended Approach Use the string constraints to choose between two pointers, a stack, frequency counts, prefix/suffix state, or dynamic programming. Maintain the invariant that processed characters have already been normalized, counted, or matched according to the operation. ## Correctness The implementation should maintain an invariant after each loop or operation that directly matches the problem statement. At termination, that invariant implies the returned value has considered every valid candidate exactly once, or has preserved the required data-structure state after every API call. ## Complexity Most direct string scans are O(n) time. Space ranges from O(1) for two pointers to O(n) for stacks, maps, or DP tables. ## Edge Cases and Tests Empty string, length 1, repeated characters, invalid characters, case sensitivity, Unicode vs ASCII, and very long input.

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|Home/Coding & Algorithms/Coinbase

Recommend movies by shared ratings

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Coinbase
Aug 7, 2025, 12:00 AM
MediumSoftware EngineerTechnical ScreenCoding & Algorithms
5
0

Recommend movies by shared ratings

Write a function recommendations(user, ratings) that returns a list of movies to recommend to the given user based on shared preferences. Each rating is a triplet [User Name, Movie Name, Rating] where Rating ∈ {1,2,3,4,5} (strings). Define two users as having similar taste if they have both rated the same movie with a 4 or 5. Recommend a movie to the user if the user has not rated it and any similar-taste user rated it a 4 or 5. Ensure the output contains unique movie names and justify any ordering you choose.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify input sizes, value ranges, mutability, return format, and tie-breaking.
  • State the target time and space complexity before coding.
  • Call out edge cases such as empty inputs, duplicates, invalid values, overflow, and boundary sizes.

What a Strong Answer Covers

  • A clear algorithm with the right data structures and enough pseudocode or code-level detail to implement it.
  • A correctness argument that explains why the algorithm covers all required cases.
  • Time and space complexity, plus at least one alternative approach when relevant.
  • Focused tests for normal cases, edge cases, and failure modes.

Follow-up Questions

  • How would the approach change if the input were streaming or too large for memory?
  • What invariants would you assert in production code?
  • Which tests would catch off-by-one, duplicate, or tie-breaking bugs?

Submit Your Answer to Earn 20XP

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