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Section 4 Review

You've finished Performance and Security, the fourth section of Database Testing. This page is a dedicated recap — bookmark it as a fast reference, separate from the modules themselves.

Section Summary

Database Performance Testing — recognizing a slow-query symptom by testing at realistic data volume, index awareness at a QA level, and spotting the N+1 query pattern via observable query counts ✔ Database Security Testing — least-privilege verification at the data layer, SQL injection symptom recognition with legitimate special-character input, and direct checks for sensitive data at rest — all identification and reporting, not exploit construction ✔ Backup, Recovery, and Audit Validation — why a backup job's "success" status isn't evidence of restorability, what recovery correctness actually requires, and extending trigger-coverage testing to compliance-relevant audit trails

How they build on each other: Module 10 established that realistic scale, not just correctness, is a testable dimension. Module 11 extended QA-level verification into security, using the same "verify directly, don't trust documentation" discipline this path has used since Section 2. Module 12 closed the section by combining both threads — data completeness under realistic operational conditions (a real restore) and trigger-coverage testing (Module 7) applied specifically to compliance stakes.

Performance and Security Quick Reference

QuestionWhat to Check
Is this feature's performance actually acceptable?Response time compared at small vs. realistic data volume
Does this page run more queries than it should?Query count at different result-set sizes (N+1 detection)
Does this credential have more access than it needs?Granted privileges compared against documented need
Is this input field vulnerable to injection?A legitimate value containing special characters (e.g., an apostrophe)
Is this backup actually restorable?An actual restore into an isolated environment, verified directly

Section 4 Knowledge Check

Five realistic scenarios. For each, decide which module's framework applies, and what you'd check first. No answers are provided here. Solutions: Section 4 Solutions.

Scenario 1: A dashboard page that lists a customer's 25 loan documents seems to run one query per document.

Scenario 2: A read-only reporting tool's database credential should never need write access to any table.

Scenario 3: A "customer notes" text field, when tested with a legitimate name like D'Souza, returns a database error.

Scenario 4: A backup job has shown a green "success" status every night for six months.

Scenario 5: A feature loads instantly for every test account, all of which have fewer than 20 transactions.

Continue to Section 5

Application Modules & Capstone, starting with AtlasBank Database Validation — where this entire path's toolkit is applied together against realistic, full-scale scenarios, closing with a capstone that traces the same compliance defect three other learning paths have already found, this time from the data layer itself.