Find Minimum Compatible Version
Company: OpenAI
Role: Machine Learning Engineer
Category: Coding & Algorithms
Difficulty: medium
Interview Round: Onsite
You are given a list of software versions sorted in ascending numeric order and an expensive predicate `is_compatible(version)`. Return the minimum version that satisfies the requirement, or `None` if no version works.
The interview usually progresses through three parts:
1. Base version
- The predicate is globally monotone: all earlier versions return `False`, and once a version returns `True`, all later versions also return `True`.
- Find the first compatible version.
2. Call-budget version
- Same monotonicity assumption as Part 1.
- The interviewer tracks how many times you call `is_compatible`, so you should minimize API calls.
3. Layered-monotonic version
- The global sequence is not necessarily monotone.
- Versions are triples `(major, minor, patch)`.
- For a fixed `(major, minor)`, compatibility over `patch` is monotone.
- At the `major` and `minor` levels, representative checks allow you to binary-search candidate groups.
- Use this layered monotonicity to find the minimum compatible version with few predicate calls.
The core skills are binary search, careful version ordering, and adapting search strategy when monotonicity only holds within subranges.
Quick Answer: This question evaluates binary search, monotonic predicates, careful version ordering, and cost-aware optimization of expensive compatibility checks. It is commonly asked in the Coding & Algorithms domain to test reasoning about monotonicity, minimizing API calls, and adapting search strategies when monotonicity holds only within subranges; the level of abstraction combines conceptual understanding of monotone properties with practical application of efficient search techniques.