## Problem Implement a function that expands `${VARIABLE}` placeholders in a template string using a provided variable map. Undefined variables should raise an error. Nested expansions (a variable whose value contains another `${...}`) should be recursively resolved up to a max depth. ```python def expand_variables( template: str, variables: dict[str, str], max_depth: int = 10 ) -> str: pass ``` **Example:** ``` variables = {"NAME": "Alice", "GREETING": "Hello, ${NAME}!", "CITY": "NYC"} expand_variables("${GREETING} From ${CITY}.", variables) -> "Hello, Alice! From NYC." expand_variables("Hi ${UNKNOWN}", variables) -> raises KeyError or UndefinedVariableError # Cycle: A -> "${B}", B -> "${A}" -> raises RecursionDepthError after max_depth ``` ## Follow-ups 1. How do you detect cycles in variable expansion, and what error do you raise? 2. How would you support default values with `${VAR:-default}` syntax (similar to bash)? 3. What is the difference between eager expansion (expand everything at parse time) and lazy expansion (expand at use time)? 4. How would you make the function safe against injection attacks if variable values come from untrusted user input?

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Variable Expansion: Implement Shell-Style Variable Substitution in a Template String

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Problem Implement a function that expands ${VARIABLE} placeholders in a template string using a provided variable map. Undefined variables should raise an error. Nested expansions (a variable whose value contains another ${...}) should be recursively resolved up to a max depth. Example: Follow-ups How do you detect cycles in variable expansion, and what error do you raise? How would you support default values with ${VAR:-default} syntax (similar to bash)? What is the difference between eager exp…

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This question was reported by a candidate who interviewed at Rubrik. 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 Rubrik are the higher-signal extractions to take from this report.

For broader preparation context, the Rubrik 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 Rubrik reports consistently are the ones worth investing in; one-off niche problems are not.

During Your Rubrik 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 Rubrik 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.