Diagnose Return Eligibility Scoring Bugs

You are working on an e-commerce return-eligibility service. For each return request, the service computes a risk score using signals such as:

• how many items the customer has returned before,
• the value of the item,
• how long the customer account has been active,
• item category and past fraud/abuse signals.

If the risk score is too high, the item should be marked as not returnable. Recently, the system has incorrectly allowed some high-risk items to be returned.

In an AI-assisted debugging round, explain how you would investigate the issue and identify six concrete classes of defects that could cause these false approvals. For each defect, describe how to detect it, how to fix it, and how to prevent it from recurring.