WBJECA 2025 — Computer PYQ
WBJECA | Computer | 2025which metric gives the best measure of efficiency in a defect discovery process across software development phases?
Choose the correct answer:
- A.
Defect Density
- B.
Cyclomatic Complexity
- C.
Defect Removal Efficiency (DRE)
(Correct Answer) - D.
Mean Time to Failure (MTTF)
Defect Removal Efficiency (DRE)
Explanation
Defect Removal Efficiency (DRE) is the primary metric used to measure the ability of a development team and its processes to identify and remove defects before the software reaches the end-user. It provides a clear indication of the thoroughness of the testing phases.
To calculate the efficiency of defect removal, we use the following formula:
DRE=E+DE
Where:
E represents the number of defects found during a specific phase (e.g., unit testing).
D represents the number of defects found by the customer or in later phases that should have been caught in the current phase.
Why other options are incorrect:
Defect Density: Measures the number of confirmed defects in a software component during development, typically relative to the size (e.g., per 1000 lines of code). It measures quality, not the efficiency of the discovery process itself.
Cyclomatic Complexity: A quantitative measure of the number of linearly independent paths through a program's source code. It is used to indicate code complexity, not defect discovery efficiency.
Mean Time to Failure (MTTF): A reliability metric that measures the average time a system operates before a failure occurs.
By maximizing the DRE, organizations can ensure that fewer bugs "leak" into production, directly reflecting the efficiency of the testing and development lifecycle:
EfficiencyProcess∝DRE

