## Problem Given a list of words and a line width `W`, implement full text justification (like a word processor). Words on each line (except the last) must be spaced so the total line length equals exactly `W`. Spaces are distributed as evenly as possible; if uneven, extra spaces go to the leftmost gaps. The last line is left-justified with single spaces. ```python def full_justify(words: list[str], W: int) -> list[str]: pass ``` ## Example ``` Input: words = ["This", "is", "an", "example", "of", "text", "justification."] W = 16 Output: ["This is an", "example of text", "justification. "] ``` ## Follow-ups 1. How does your greedy line-breaking strategy perform vs. dynamic programming (Knuth-Plass)? 2. Extend to support RTL (right-to-left) text. 3. How would you handle words longer than `W`? 4. In a mobile layout context (variable-width fonts), how does the algorithm change?

InterviewDB Question

String Layout: Word Wrap and Text Justification in a Fixed-Width Container

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Question Details

Problem Given a list of words and a line width W, implement full text justification (like a word processor). Words on each line (except the last) must be spaced so the total line length equals exactly W. Spaces are distributed as evenly as possible; if uneven, extra spaces go to the leftmost gaps. The last line is left-justified with single spaces. Example Follow-ups How does your greedy line-breaking strategy perform vs. dynamic programming (Knuth-Plass)? Extend to support RTL (right-to-left) t…

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About This Question

This is a reported interview question from a robinhood interview during the onsite round.

It covers the following topics: Strings, Frontend, Dynamic Programming, Ios, Greedy, Android, System Design, Coding, Onsite .

Topics

Strings Frontend Dynamic Programming Ios Greedy Android System Design Coding Onsite

About Robinhood Interview Reports

This question was reported by a candidate who interviewed at Robinhood. LeakCode aggregates interview reports from 10+ sources, including 1Point3Acres, Glassdoor, LeetCode Discuss, Blind, Reddit, Indeed, and Nowcoder. Each report is translated where necessary, deduplicated against existing entries, and tagged by company, role, round type, and reporting date.

Use this question as one calibration data point, not a memorization target. Companies typically rotate their question pools every 2-4 months; the exact wording of a 2024 question may differ from what you encounter today. The underlying pattern, difficulty level, and follow-up depth at Robinhood are the higher-signal extractions to take from this report.

For broader preparation context, the Robinhood interview process typically includes a recruiter screen, one or two technical phone screens, and a 4-5 round on-site loop covering coding, system design (at L4+ levels), and behavioral. Reports tagged on LeakCode show the round-by-round distribution and typical difficulty calibration. To browse questions filtered by round type and seniority, use the company hub linked above.

How To Practice This Type of Question

Solve similar problems on LeetCode under timed conditions (25-35 minutes per medium difficulty). The goal is pattern recognition: recognize the underlying technique (sliding window, two-pointer, BFS, memoized recursion, etc.) within 60-90 seconds of reading. Strong candidates verbalize their hypothesis out loud before coding, then iterate based on feedback. Weak candidates dive into implementation immediately, lose time on the wrong approach, and run out of time for follow-ups.

Companies update their question pools every 2-4 months. The exact wording of any given question may have been retired by the time you interview. Focus your prep on the pattern, not the specific problem. The patterns that appear in Robinhood reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Robinhood Round

Apply the standard interview round template: clarify requirements (2-3 minutes), state your approach out loud and confirm direction with the interviewer (3-5 minutes), code with narration (15-25 minutes), test with concrete examples including edge cases (5 minutes), discuss optimization or trade-offs if time permits (5 minutes). This template is universally accepted across FAANG and adjacent companies; deviating from it produces weaker interviewer feedback signal.

The single most predictive failure mode in Robinhood reports tagged "no hire": not asking clarifying questions. Interviewers are explicitly trained to weight this. Strong candidates ask 3-5 clarifying questions even on problems that look obvious; weak candidates dive into code immediately. The clarifying-question check is often the first signal recorded in the interviewer's written notes.