ISTQB_Managing the Product_2.3 Defect Management_TM-2.3.6 (K2) Explain how defect report statistics can be used to devise process improvement

 

Key Concepts of TM-2.3.6

Key ConceptExplanation
Defect Report AnalysisDefect reports provide insights into software quality and testing effectiveness.
Phase ContainmentDetermines how well defects are contained within their originating phase.
Cost of Quality AnalysisIdentifies the cost of detecting/fixing defects at different stages.
Defect Root Cause Analysis (RCA)Finds the underlying reasons for defect introduction.
Defect ClusteringIdentifies modules with high defect densities to guide risk-based testing.
Reopened DefectsUsed to assess debugging and fixing quality.
Duplicate/Rejected DefectsUsed to assess clarity and precision of defect reporting.
Data-Driven ImprovementsWell-maintained defect data helps continuous improvement.

📊 Summary Table with Examples

Improvement AreaWhat to AnalyzeExample Use
Phase ContainmentIntroduction vs Detection phase70% of UI defects found during system test → Improve UI unit tests
Cost of QualityFixing cost per phaseDefects fixed in UAT cost 5x more → Shift-left testing
Root Cause AnalysisCoding vs Requirements issues60% defects from poor specs → Improve requirement workshops
Defect ClusteringModules with frequent defectsModule X has 30% defects → Re-factor Module X
Reopened DefectsNumber reopened after closing10% reopened → Improve fix validation
Duplicate DefectsSame defect reported twiceMany duplicates → Train testers in proper reporting
Rejected DefectsValidity of reported defects15% false defects → Align test & dev understanding

🧠 Mind Map for Quick Revision

pgsql
Defect Report Data │ ├─ Phase Containment │ └─ Improve early defect detection │ ├─ Cost of Quality │ └─ Reduce late-phase fix costs │ ├─ Root Cause Analysis │ └─ Prevent recurring issues │ ├─ Defect Clustering │ └─ Focus on high-risk modules │ ├─ Reopened Defects │ └─ Review debugging process │ ├─ Duplicate/Rejected Defects │ └─ Improve defect reporting quality │ └─ Metrics Utilization └─ Enable data-driven process improvement

🎯 Scenario-Based MCQs (K2)

Short Scenario-Based MCQs

Q1: During a retrospective, you notice many defects are being introduced during the requirements phase. What is a good process improvement?
A. Increase unit testing
B. Improve requirement reviews ✅
C. Reduce UAT effort
D. Focus on UI automation

Q2: A team reports a high number of reopened defects. What does this indicate?
A. Test cases are too simple
B. Developers aren’t fixing issues
C. Debugging quality needs review ✅
D. Code coverage is high


Long Scenario-Based MCQs

Q3: Your team analyzes defect logs and observes that 40% of all defects are from one component. This component also required rework after every sprint. What is the best process improvement?
A. Add more testers to that component
B. Re-factor the component and increase unit testing ✅
C. Ignore it since rework is expected
D. Increase logging statements in code

Q4: After reviewing defect trends, you notice many rejected and duplicate defects. What could be improved?
A. Increase exploratory testing
B. Improve regression suite
C. Provide better defect reporting training to testers ✅
D. Involve customers more in triage

Q1: Phase Containment

Scenario:
In your project, 70% of the design-phase defects are detected only during system testing. This has increased rework and delayed releases.

Options:
A. Increase UI automation
B. Introduce formal peer reviews during design
C. Reduce system testing effort
D. Start testing only after development ends

Answer:
B. Introduce formal peer reviews during design


Q2: Cost of Quality

Scenario:
Analysis shows that fixing a defect in production costs NOK 12,000, whereas the same defect would cost only NOK 2,000 if caught during integration testing.

Options:
A. Eliminate unit testing to save time
B. Shift more testing effort to earlier phases
C. Delay testing until feature complete
D. Increase UAT testing effort

Answer:
B. Shift more testing effort to earlier phases


Q3: Root Cause Analysis

Scenario:
During the retrospective, root cause analysis indicates that over 50% of the reported defects were due to unclear or incomplete requirements.

Options:
A. Hire more testers
B. Introduce early validation of requirements with stakeholders
C. Postpone testing until requirements are clear
D. Add more exploratory testing sessions

Answer:
B. Introduce early validation of requirements with stakeholders


Q4: Defect Clustering

Scenario:
Reports show that 30% of all defects are located in Module Z, a core part of your application. The same module has been problematic across multiple sprints.

Options:
A. Ignore since it is already tested
B. Re-factor Module Z and strengthen targeted tests
C. Skip testing Module Z in future cycles
D. Add more logging to the module

Answer:
B. Re-factor Module Z and strengthen targeted tests


Q5: Reopened Defects

Scenario:
Defect data reveals that 18% of all resolved defects are being reopened due to incomplete fixes.

Options:
A. Reduce regression testing
B. Assign all bugs to a single developer
C. Improve fix validation and test coverage during re-tests
D. Mark reopened defects as new bugs

Answer:
C. Improve fix validation and test coverage during re-tests


Q6: Duplicate and Rejected Defects

Scenario:
Testers are logging a large number of duplicate and rejected defects. Developers complain about wasting time triaging these.

Options:
A. Use automation to reduce testing
B. Train testers on accurate and effective defect reporting
C. Let developers reject bugs without justification
D. Set priority of all new bugs to low

Answer:
B. Train testers on accurate and effective defect reporting


Q7: Missing Defect Tracking

Scenario:
Your team skips tracking unit-level defects to avoid overhead. Management is now asking for root cause data.

Options:
A. Use production data to guess the defect origin
B. Start tracking all defects across all phases for better visibility
C. Track only showstopper defects
D. Wait until testing ends to document everything

Answer:
B. Start tracking all defects across all phases for better visibility


Q8: Debugging Quality

Scenario:
A pattern of reopened defects suggests that many issues aren’t being completely resolved in the first attempt.

Options:
A. Ask testers to log more detailed defects
B. Improve the developer debugging and fix validation process
C. Increase code review frequency
D. Reduce test cycles

Answer:
B. Improve the developer debugging and fix validation process


Q9: Defect Prevention

Scenario:
Frequent copy-paste errors are introducing similar bugs across the application.

Options:
A. Conduct weekly manual code reviews
B. Use static analysis tools and enforce coding standards
C. Reduce developer workload
D. Only allow senior developers to commit code

Answer:
B. Use static analysis tools and enforce coding standards


Q10: Process Visibility

Scenario:
Your team doesn't log any low-severity defects. During the review, you're asked to evaluate defect trends for improvement suggestions.

Options:
A. Continue the same approach to reduce effort
B. Begin logging all defects to provide comprehensive analysis
C. Only log defects found in UAT
D. Ask QA to guess defect origins from memory

Answer:
B. Begin logging all defects to provide comprehensive analysis


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