← rippling Interview Insights

rippling·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jun 2026

Summary

Rippling SWE interview with a delivery cost calculation problem. Pretty standard coding round but there were a few design decisions that came up mid-question that I wasn't fully expecting.

Questions Asked (1)

Q1

Design a delivery cost calculator with methods to add a driver (each with their own hourly rate), record a delivery with a start and end time, and compute the total cost across all deliveries.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

The core logic isn't that bad but I got tripped up when they asked how I'd handle the time inputs.

Create a free account to read the full note

AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and defining the core entities (Driver, Delivery) and their relationships. Then design the class structure with methods to add drivers, record deliveries, and compute total cost, ensuring correct handling of time and rates. Finally, discuss trade-offs and potential optimizations.

Pro tip: Mention that you would store durations in minutes or seconds to avoid floating-point precision issues with hours, and consider using integer cents for monetary calculations to prevent rounding errors.

1. Clarify Requirements

Ask questions to understand constraints: Are drivers assigned to deliveries? Can a delivery span multiple drivers? What is the expected scale? Should costs be computed on-the-fly or aggregated?

2. Define Data Models

Design classes for Driver (id, hourlyRate) and Delivery (driverId, startTime, endTime). Consider using immutable objects and appropriate data types (e.g., LocalDateTime, BigDecimal).

3. Design Calculator Class

Create a DeliveryCostCalculator class with methods: addDriver(Driver), recordDelivery(Delivery), and getTotalCost(). Internally, maintain a map of drivers and a list of deliveries.

4. Implement Cost Computation

For each delivery, compute duration (end - start) in hours, multiply by driver's hourly rate, and sum. Handle edge cases like overlapping deliveries or invalid times.

5. Discuss Trade-offs and Extensions

Talk about time complexity (O(n) for total cost), potential concurrency issues, and how to extend for features like discounts, taxes, or real-time updates.

Key Points to Mention

  • Use precise time handling (e.g., Duration in Java, timedelta in Python) to avoid floating-point errors.
  • Store monetary values as integers (cents) or use BigDecimal to prevent rounding issues.
  • Consider thread safety if multiple threads might add drivers or deliveries concurrently.
  • Discuss whether to compute total cost eagerly (on each record) or lazily (on demand) and the trade-offs.
  • Mention validation: ensure end time is after start time, driver exists, etc.
  • Extensibility: how to add features like different rates for overtime or multiple drivers per delivery.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.