What technique helps prevent duplicate records when clients retry requests in an address API?

What technique helps prevent duplicate records when clients retry requests in an address API?

• A. Idempotent design using PUT/DELETE
• B. Random IDs
• C. Logging
• D. No practice

Answer: (A)

Idempotence means that applying the same operation multiple times has the same effect as doing it once. When a client retries a request, you don’t want to create duplicates, so the operation should be safe to repeat. Using PUT or DELETE with idempotent semantics achieves this. PUT creates or replaces a resource at a known URL, so sending the same PUT payload again leaves the resource in the same state as the first attempt—no extra record is created. DELETE also behaves idempotently: deleting the resource multiple times just ensures it’s gone, without making additional data. This combination prevents duplicates during retries. Random IDs could still lead to duplicates or inconsistent state; logging helps diagnose issues but doesn’t prevent duplicates; doing nothing wouldn’t protect against retries creating duplicates.

Idempotence means that applying the same operation multiple times has the same effect as doing it once. When a client retries a request, you don’t want to create duplicates, so the operation should be safe to repeat.

Using PUT or DELETE with idempotent semantics achieves this. PUT creates or replaces a resource at a known URL, so sending the same PUT payload again leaves the resource in the same state as the first attempt—no extra record is created. DELETE also behaves idempotently: deleting the resource multiple times just ensures it’s gone, without making additional data. This combination prevents duplicates during retries.

Random IDs could still lead to duplicates or inconsistent state; logging helps diagnose issues but doesn’t prevent duplicates; doing nothing wouldn’t protect against retries creating duplicates.