The objective of this study is the identification of factors that influence defect injection and defect detection. The study is part of a broader research project with the goal to lower the number of residual defects in software intensive products, by using the influencing factors to decrease injection of defects and to increase detection of defects. As a first step, we performed an extensive literature search to find influencing factors and processed the factors to achieve consistently formulated sets of factors without duplications. As a second step, we used a cluster analysis to reduce the number influencing factors to manageable-sized sets for practical application. As a last step, final groupings of factors were obtained by expert interpretation of the cluster analysis results. These steps were separately performed for defect injection and detection influencing factors, resulting in sets of, respectively, 16 and 17 factors. Finally, the resulting factor groupings were evaluated. The findings (1) are the basis for further research focusing on a framework for lowering residual defects, (2) already provide information to enable practitioners to devise strategies for lowering residual defects, and (3) may create awareness in organizations to reconsider policies regarding development and Verification & Validation.
['Jef Jacobs', 'Jan van Moll', 'Rj Rob Kusters', 'Jos J. M. Trienekens', 'Ac Aarnout Brombacher']
Identification of factors that influence defect injection and detection in development of software intensive products