DoorDash·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say

Jun 2026Remote

Summary

DoorDash SWE coding round, one meaty implementation question about cart validation. Felt like a design-meets-coding hybrid more than a pure algorithm problem, which I wasn't fully expecting.

Questions Asked (1)

Implement a cart validation function for a food delivery app. Given a cart (list of items with itemId and quantity) and a catalog (with availableQuantity, minQuantity, maxQuantity per item), validate the cart and return a structured result with an isValid flag and a list of errors.

System DesignTechnical Trade-offsAlgorithms & Data Structures

Author's notes

The base checks weren't hard to code up but I got tripped up deciding whether to fail fast or collect all errors.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and edge cases, then outline a validation algorithm that checks each cart item against the catalog for existence, quantity limits, and duplicates. Discuss trade-offs between approaches (e.g., hash map vs. sorting) and how to structure the result for extensibility and performance.

Pro tip: Proactively mention how you would handle concurrency or stale catalog data, and suggest adding logging/metrics for validation failures to improve observability in production.

1. Clarify Requirements and Edge Cases

Ask questions to understand expected behavior for missing items, duplicate cart entries, zero/negative quantities, and whether catalog data is static or dynamic. Confirm the exact structure of the result and error messages.

2. Design the Validation Algorithm

Propose an efficient approach: build a hash map from the catalog for O(1) lookups, then iterate through the cart to validate each item. Consider handling duplicates by aggregating quantities or flagging them as errors.

3. Define Error Handling and Result Structure

Specify the error types (e.g., ITEM_NOT_FOUND, QUANTITY_BELOW_MIN, QUANTITY_ABOVE_MAX, DUPLICATE_ITEM) and how they map to the isValid flag. Ensure the result is easily consumable by the caller.

4. Analyze Complexity and Trade-offs

Discuss time and space complexity (O(n+m) with hash map) and compare with alternatives like sorting or database queries. Mention scalability considerations for large carts or catalogs.

5. Extend and Test

Suggest how to extend the solution for future requirements (e.g., item substitutions, promotions) and outline test cases covering normal, boundary, and error scenarios.

Key Points to Mention

Use a hash map for O(1) catalog lookups to achieve O(n+m) time complexity.
Handle duplicate cart items by aggregating quantities or reporting an error, and clarify the expected behavior.
Validate against minQuantity, maxQuantity, and availableQuantity, and consider if availableQuantity should be checked against the total requested quantity.
Return a structured result with an isValid boolean and a list of error objects containing itemId and error type for easy debugging.
Consider concurrency and stale data: mention optimistic locking or re-validation at checkout to handle inventory changes.
Add logging and metrics for validation failures to monitor system health and user behavior.

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