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Design a bus simulation metric

Last updated: Apr 6, 2026

Quick Overview

This question evaluates a candidate's ability to comprehend and navigate a large unfamiliar codebase, safely make targeted code changes, and design, instrument, and validate a meaningful simulation efficiency metric, covering code comprehension, incremental development, and measurement design.

  • hard
  • Instacart
  • Software Engineering Fundamentals
  • Software Engineer

Design a bus simulation metric

Company: Instacart

Role: Software Engineer

Category: Software Engineering Fundamentals

Difficulty: hard

Interview Round: Onsite

In an AI-assisted interview, you are given an unfamiliar codebase of roughly 10,000 lines that implements a bus traffic simulation. You may use an approved AI assistant to search the codebase, summarize files, and help locate logic. You are asked to: (1) explain the responsibility of specific classes and identify where particular behaviors are implemented, (2) make small targeted code changes safely, and (3) design and implement a new metric for simulation efficiency. Describe a strong end-to-end approach for understanding the codebase quickly, validating AI-generated answers, choosing a meaningful efficiency metric, instrumenting the simulator, and testing the result.

Quick Answer: This question evaluates a candidate's ability to comprehend and navigate a large unfamiliar codebase, safely make targeted code changes, and design, instrument, and validate a meaningful simulation efficiency metric, covering code comprehension, incremental development, and measurement design.

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Instacart logo
Instacart
Jan 29, 2026, 12:00 AM
Software Engineer
Onsite
Software Engineering Fundamentals
5
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In an AI-assisted interview, you are given an unfamiliar codebase of roughly 10,000 lines that implements a bus traffic simulation. You may use an approved AI assistant to search the codebase, summarize files, and help locate logic. You are asked to: (1) explain the responsibility of specific classes and identify where particular behaviors are implemented, (2) make small targeted code changes safely, and (3) design and implement a new metric for simulation efficiency. Describe a strong end-to-end approach for understanding the codebase quickly, validating AI-generated answers, choosing a meaningful efficiency metric, instrumenting the simulator, and testing the result.

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