WBJECA 2025 — Computer PYQ

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:

$$DRE=\frac{E}{E+D}$$

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:

$$Efficienc{y}_{Process}\propto DRE$$