DoorDash·Software Engineer·Technical Phone Screen·Intermediate

Intermediate

May 2026Remote

Summary

DoorDash SWE coding screen, pretty standard setup except the question wasn't what I'd prepped for at all. Felt the time pressure hard by the end.

Questions Asked (1)

Design a cart validation function that checks item quantity availability and enforces minimum/maximum purchase limits.

Algorithms & Data StructuresTechnical Trade-offsAdaptability & Ambiguity

Author's notes

I'd drilled the dasher payment and bootstrap problems so much that seeing this felt like a gut punch.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and assumptions, then outline a modular design that separates concerns: inventory check, min/max limits, and error handling. Walk through the algorithm with a concrete example, discuss trade-offs (e.g., performance, scalability), and mention edge cases and extensibility.

Pro tip: Demonstrate awareness of real-world constraints like concurrency and stale inventory data, and propose idempotent validation with clear error codes for client-side handling.

1. Clarify Requirements

Ask questions to understand the scope: What are the inputs (cart, inventory)? Are min/max limits per item or per order? How should errors be reported? This shows you avoid assumptions.

2. Define Data Structures

Specify the cart and inventory representations (e.g., maps of item ID to quantity). Consider if inventory is a simple count or has other constraints (e.g., per-user limits).

3. Design Validation Logic

Outline the algorithm: iterate through cart items, check availability against inventory, and enforce min/max limits. Handle missing items and aggregate errors.

4. Discuss Trade-offs and Edge Cases

Talk about performance (O(n) vs. O(1) lookups), concurrency (race conditions), and edge cases (empty cart, zero inventory, limits not set). Mention how to extend for future needs.

5. Summarize and Test

Recap the design, and suggest test cases (e.g., item over max, under min, out of stock). This shows thoroughness and quality focus.

Key Points to Mention

Separation of concerns: validation logic should be independent of data fetching.
Error handling: return structured errors with item IDs and reasons (e.g., 'OUT_OF_STOCK', 'EXCEEDS_MAX').
Performance: use hash maps for O(1) inventory lookups; consider batch validation for multiple items.
Concurrency: inventory may change between validation and checkout; suggest optimistic locking or re-validation.
Extensibility: design to easily add new rules (e.g., item substitutions, time-based limits).
Testing: include unit tests for boundary conditions (exactly at min/max, zero quantity).

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