CTC Data Analysis & Reporting 2 — Questions and Answers
Question 1: A test conductor notices that defect detection rates dropped significantly after the third test cycle. Which statistical technique best helps determine whether this trend is meaningful?
- Control chart analysis (Correct answer)
- Pareto chart ranking
- Scatter plot correlation
- Histogram binning
Correct answer: Control chart analysis
Control charts distinguish between common-cause variation and statistically significant shifts in a process over time.
Question 2: When computing test pass rate, a team divides passed test cases by total executed test cases. What critical data point is this formula missing?
- Blocked test cases (Correct answer)
- Test execution time
- Tester experience level
- Requirement priority
Correct answer: Blocked test cases
Blocked test cases are neither passed nor failed but were not executed, so excluding them inflates the apparent pass rate.
Question 3: A CTC report shows high requirement coverage but low defect detection effectiveness. Which conclusion is most appropriate?
- Test cases may lack depth and only verify happy paths (Correct answer)
- The development team has produced high-quality code
- Requirements were poorly defined from the start
- Test automation is covering most of the scenarios
Correct answer: Test cases may lack depth and only verify happy paths
High coverage with low defect detection often indicates shallow tests that execute requirements without probing edge cases or negative scenarios.
Question 4: In a test summary report, the 'residual risk' section communicates what information to stakeholders?
- Known issues and untested areas remaining at release (Correct answer)
- Total budget spent versus planned budget
- Number of test cases created per tester
- Regression test execution velocity
Correct answer: Known issues and untested areas remaining at release
Residual risk quantifies the exposure remaining after testing due to unresolved defects, scope gaps, or untested functionality.
Question 5: Which metric directly measures how efficiently a test team finds defects relative to the effort invested?
- Defect detection percentage (DDP) (Correct answer)
- Defect removal efficiency (DRE)
- Mean time to detect (MTTD)
- Test execution rate
Correct answer: Defect detection percentage (DDP)
DDP measures the proportion of total defects that testing found compared to all defects discovered (including those found post-release).
Question 6: A manager requests a report showing which product modules have the highest defect density. What two data inputs are required?
- Defect count per module and module size (lines of code or function points) (Correct answer)
- Defect severity and tester assignment per module
- Test execution time and number of test cases per module
- Defect priority and requirement count per module
Correct answer: Defect count per module and module size (lines of code or function points)
Defect density = defects found / size of the module, so both the defect count and a size measure are needed.
Question 7: When a test conductor reviews a burn-down chart for a sprint and sees the actual line plateau for two days, what does this most likely indicate?
- Test execution has stalled, possibly due to blockers or resource issues (Correct answer)
- The team has completed all planned test cases ahead of schedule
- Defect fix velocity has exceeded the test execution rate
- The sprint backlog was accurately estimated
Correct answer: Test execution has stalled, possibly due to blockers or resource issues
A flat plateau on a burn-down chart means work remaining is not decreasing, signaling execution impediments that need investigation.
CTC Data Analysis & Reporting 2
A test conductor notices that defect detection rates dropped significantly after the third test cycle.
Which statistical technique best helps determine whether this trend is meaningful?