Solve tree partition and IPO allocation
Company: Two Sigma
Role: Machine Learning Engineer
Category: Coding & Algorithms
Difficulty: Medium
Interview Round: Take-home Project
Quick Answer: This question evaluates algorithmic problem-solving skills in tree processing and allocation simulations, specifically assessing understanding of subtree-sum computation for tree partitioning and deterministic round-robin allocation logic for IPO-style share distribution, along with appropriate data structure selection and correctness under edge cases. It is commonly asked in the Coding & Algorithms domain because it measures practical application-level implementation and the ability to analyze time and space complexity rather than purely conceptual proof.
Minimum Difference Tree Partition
Constraints
- Inputs are provided as Python literals matching the function signature.
- Return a deterministic exact-match result.
Examples
Input: ([-1,0,0,1,1,2], [1,2,2,1,1,1])
Expected Output: 0
Explanation: Prompt example.
Input: ([-1,0], [5,1])
Expected Output: 4
Explanation: Single cut.
Input: ([-1], [5])
Expected Output: 0
Explanation: No edge to cut.
Hints
- Choose a representation that makes the core operation simple.
- Handle empty and boundary inputs before the main algorithm.
IPO Share Allocation by Price Tier
Constraints
- Inputs are provided as Python literals matching the function signature.
- Return a deterministic exact-match result.
Examples
Input: (5, [[1,3,10,1], [2,3,10,2], [3,5,9,1]])
Expected Output: [3, 2, 0]
Explanation: Round-robin within top tier.
Input: (4, [[1,10,8,1]])
Expected Output: [4]
Explanation: Single bidder group.
Input: (0, [[1,1,1,1]])
Expected Output: [0]
Explanation: No shares.
Hints
- Choose a representation that makes the core operation simple.
- Handle empty and boundary inputs before the main algorithm.