How would you test concurrency issues when multiple users update the same address?

• A. Lock the database table globally during updates.
• B. Use optimistic locking or version checks, simulate concurrent updates, and handle conflicts with clear messages.
• C. Ignore concurrency and resolve conflicts with manual intervention.
• D. Always clone the address to a new row before any update.

Answer: (B)

Concurrency testing for updates to the same address relies on a strategy that detects conflicts without blocking everyone all the time. Optimistic locking uses a version field (or a timestamp) on the address record. When you read the address, you also read its version. When you submit an update, you include that version and require the current version in the update condition. If another user updated the address in the meantime, the version has changed, so the update affects zero rows and you know a conflict occurred. This lets you surface a clear message to the user and offer a retry or a merge workflow, rather than forcing everyone to wait or risk data loss.

To test this, simulate two users editing the same address concurrently: both read the address and its version, one updates and commits, then the other tries to update using the old version. The second update should be rejected with a concurrency conflict, prompting the application to show a user-friendly message and an option to retry. Automated tests can reproduce this by running two parallel transactions or threads against the same address and verifying the conflict path and retry logic.

Why not lock the whole table? Global locking kills parallelism and hurts performance; it’s not practical for concurrent user scenarios. Why not always clone the address to a new row? Creating a new row for every update adds complexity and overhead and isn’t the standard way to resolve conflicts; versioning with conflict handling is typically lighter and clearer for end users, while history can be captured separately if needed.