Defect Detection Efficiency

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.

ISTQB Definition

  • 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.


Formula 1

  • DDE = (Number of Defects Detected in a Phase / Total Number of Defects) x 100 %

Formula 2

  • DDE = (Number of Defects Detected Prior to a Phase / Total Number of Defects) x 100 %


Phase Defects Detected DDR (Formula 1) DDR (Formula 2)
Unit Testing 20 15.2% 15.2%
Integration Testing 12 9.1% 24.2%
System Testing 82 62.1% 86.4%
Acceptance Testing 15 11.4% 97.7%
Production 3 2.3% 100.0%
TOTAL 132 100.0%

Sample Interpretation:

  • 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 March 12, 2023 by STF