Uber·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

Apr 2026

Summary

Phone screen for a SWE role at Uber, design-and-code round where you build a last-click attribution tracker in memory, write the API, and run your own tests. Pretty meaty for a phone screen.

Questions Asked (1)

Build an in-memory last-click attribution tracker. You need to implement recordClick, recordConversion, getCampaignConversions, and getUserAttribution, where each conversion is attributed to the same user's most recent click within a 300-second window. Write and run your own test cases.

System DesignAlgorithms & Data StructuresAPI & Integrations

Author's notes

The part that tripped me up first was the ordering assumption.

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AI HintsAI Generated

Suggested Approach

Clarify the requirements and edge cases, then design a data structure that efficiently tracks the most recent click per user and attributes conversions within the 300-second window. Implement the methods with careful handling of timestamps, and write comprehensive tests covering normal, boundary, and edge cases.

Pro tip: Discuss the trade-offs between different data structures (e.g., hash map vs. balanced tree) and mention how you would handle out-of-order events or clock skew, showing awareness of real-world complexities.

1. Clarify Requirements and Edge Cases

Ask questions to confirm the exact behavior: What if multiple clicks occur within the window? What if a conversion happens without a prior click? How to handle out-of-order timestamps? This ensures you build the right solution.

2. Design Data Structures

Choose appropriate data structures: a hash map from user ID to their most recent click (campaign ID and timestamp), and a map from campaign ID to conversion count. Consider if you need to store all clicks or just the latest per user.

3. Implement Core Methods

Implement recordClick to update the user's latest click, recordConversion to check the time difference and attribute if within 300 seconds, and the getter methods to retrieve counts and attribution.

4. Write and Run Test Cases

Create tests for: conversion within window, conversion outside window, multiple clicks before conversion, conversion without click, multiple users, and boundary cases (exactly 300 seconds). Run them to verify correctness.

5. Analyze Complexity and Discuss Improvements

State the time and space complexity of each operation. Discuss potential optimizations or extensions, such as handling out-of-order events or scaling to distributed systems.

Key Points to Mention

Time complexity: O(1) for recordClick and recordConversion using hash maps.
Space complexity: O(U + C) where U is number of users and C is number of campaigns.
Handling of the 300-second window: use timestamps and check difference <= 300.
Edge cases: conversion without click, multiple clicks, exactly 300 seconds, out-of-order events.
Data structure choice: hash map for O(1) access, but consider if you need to store all clicks for other queries.
Testing strategy: unit tests covering normal, boundary, and error cases.

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