Lost update problem definition: is it when User A reads data that come from a partial (uncommitted) transaction of User B?

Introduction / Context:
Classic anomalies include dirty read, nonrepeatable read, phantom read, and lost update. Each has a precise definition. This question verifies whether you can accurately state what “lost update” means.

Given Data / Assumptions:

• Dirty read: reading uncommitted data.
• Nonrepeatable read: seeing a row change between two reads in the same transaction.
• Lost update: two transactions update the same data; one overwrites the other without awareness.

Concept / Approach:
The statement provided describes a dirty or inconsistent read rather than a lost update. A lost update requires conflicting writes where one transaction’s update is effectively undone or overwritten by another committed update.

Step-by-Step Solution:
Compare definitions: “reads uncommitted” → dirty read; “overwritten writes” → lost update.The statement talks about User A reading data processed by part of User B’s transaction → that is dirty/inconsistent read.Therefore, this is not the lost update definition and the statement is invalid.

Verification / Alternative check:
Simulate two UPDATEs without proper isolation; observe last writer wins and one change is lost—this is the lost update scenario, not merely a read of uncommitted data.

Why Other Options Are Wrong:
Snapshot isolation actually prevents lost updates via write-write checks; equating with nonrepeatable read is incorrect.

Common Pitfalls:
Mixing up anomaly names; thinking any anomaly with two users is “lost update.”

Final Answer:
Invalid statement