Quick Summary
- Aggregate purchase logs to build per-user profiles tracking activity days, distinct order types, and spending ranges.
- Filter users appearing on both days who have transacted in at least two different order categories.
- Calculate a composite trust score based on historical order type familiarity and amount consistency relative to past min/max bounds.
What This Tests
- Using hash maps and sets for efficient data aggregation and lookups.
- Performing set intersections and filtering based on aggregated criteria.
- Implementing mathematical scoring logic with bounds checking and percentage calculations.
- Handling string-to-number conversion and lexicographical sorting.
Common Patterns
Hashing
Sorting
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Test Cases
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Output
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