Software quality: an overview from the perspective of total quality management
IBM Systems Journal
Analysis of fault generation caused by stress during software development
Journal of Systems and Software - Special issue on achieving quality in software
An analysis of factors affecting software reliability
Journal of Systems and Software
Software Engineering Economics
Software Engineering Economics
An Instrument for Measuring the Key Factors of Successin Software Process Improvement
Empirical Software Engineering
A Ranking of Software Engineering Measures Based on Expert Opinion
IEEE Transactions on Software Engineering
Software development: processes and performance
IBM Systems Journal
Managing software quality through a hybrid defect content and effectiveness model
Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement
Proceedings of the 32nd ACM/IEEE International Conference on Software Engineering - Volume 2
Empirical Software Engineering
Defect detection effectiveness and product quality in global software development
PROFES'11 Proceedings of the 12th international conference on Product-focused software process improvement
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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.