DEFECT DETECTION EFFICIENCY (DDE) is the percentage of defects detected during a phase/stage divided by the total number of defects. Or, it can also be defined as the percentage of defects detected prior to a phase / stage.
- defect detection percentage: The number of defects found by a test level, divided by the number found by that test level and any other means afterwards.
- Are confirmed and agreed upon (not just reported).
- Dropped defects are not counted.
DDE = (Number of Defects Detected in a Phase / Total Number of Defects) x 100 %
DDE = (Number of Defects Detected Prior to a Phase / Total Number of Defects) x 100 %
|Phase||Defects Detected||DDR (Formula 1)||DDR (Formula 2)|
- DDR (Formula 1) of Unit Testing is just 15.2% and could be bettered. Earlier the detection, less costlier the solution.
- Assuming that the internal team does Unit, Integration and System testing, the DDR (Formula 2) is only 86.4% at the level of System Testing which means that the team is weak and is letting the defects slip to the customer / users (Acceptance Testing & Production).
- For measuring the quality of the processes (process efficiency) within software development life cycle; by evaluating the degree to which defects introduced during that phase/stage are eliminated before they are transmitted into subsequent phases/stages.
- For identifying the phases in the software development life cycle that are the weakest in terms of quality control and for focusing on them.
- For assessing the performance of the team / software testers. [Take extra caution while using this though; there are many factors involved in their performance and solely using this metric to judge them would be unfair.]
Learn about a somewhat related and useful metric: DEFECT AGE.
Last Updated on September 2, 2020 by STF