Stackadapt·Software Engineer·Onsite - System Design / Architecture·Intermediate

Intermediate

Apr 2026

Summary

System design round at Stackadapt for a software engineering role. The question was a multi-part thing that built on earlier validation work, and then asked you to tie it all together into an actual API design with a real discussion component. Pretty involved for a single question.

Questions Asked (1)

Using two validation functions you built earlier, design and write pseudocode for an update API for both classes. The API should accept an update payload, run the right validation, reject with all error messages if it fails, and apply the update atomically if it passes. Also discuss partial vs full update semantics, concurrency handling, and what the error response format should look like.

API & IntegrationsSystem DesignTechnical Trade-offs

Author's notes

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AI HintsAI Generated

Suggested Approach

Start by clarifying the update semantics (partial vs full) and the validation functions' contracts. Then write pseudocode that validates the entire payload first, collects all errors, and only applies changes if validation passes, using a transaction or lock for atomicity. Finally, discuss concurrency control and a consistent error response format.

Pro tip: Explicitly state your assumptions about the validation functions (e.g., they return a list of errors) and the update semantics (e.g., PATCH vs PUT) before diving into pseudocode—this shows you think about contracts and edge cases.

1. Clarify requirements and assumptions

Confirm whether the update is partial (PATCH) or full (PUT), and how the validation functions behave (e.g., return all errors or fail fast). State any assumptions about the data store and concurrency model.

2. Design the update API signature and flow

Define the API endpoint, input payload, and output. Outline the high-level flow: validate, collect errors, if errors return 400 with all messages, else apply update atomically.

3. Write pseudocode for validation and atomic update

Write clear pseudocode that calls the appropriate validation function, aggregates errors, and uses a transaction or lock to apply changes atomically. Handle both classes if needed.

4. Address concurrency and atomicity

Explain how you prevent race conditions (e.g., optimistic locking with version, pessimistic locking, or transactions) and ensure the update is all-or-nothing.

5. Define error response format and discuss trade-offs

Specify a consistent error response (e.g., JSON with error code, message, and details array). Discuss trade-offs between partial and full updates, and concurrency strategies.

Key Points to Mention

Partial vs full update semantics: PATCH merges fields, PUT replaces the entire resource; validation must account for missing fields in partial updates.
Validation strategy: run all validations and collect all errors before returning, rather than failing on the first error, to provide comprehensive feedback.
Atomicity: use database transactions or locks to ensure that either all changes are applied or none, preventing partial updates on failure.
Concurrency control: optimistic locking (version field) or pessimistic locking to handle simultaneous updates and avoid lost updates.
Error response format: consistent structure with HTTP status 400, error code, message, and an array of field-specific errors for client-side handling.
Idempotency: consider making update operations idempotent, especially for PUT, to simplify retries and concurrency.

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