Optimizing quality assurance strategies through an integrated quality assurance approach. Guiding quality assurance with assumptions and selection rules

Quality assurance activities are often still expensive or do not offer the expected quality. A recent trend aimed at overcoming this problem is tighter integration of several quality assurance techniques such as analysis and testing in order to exploit synergy effects and thus reduce costs or improve the coverage of quality assurance activities. However, one main challenge in exploiting such benefits is that knowledge about the relationships between many different factors is needed, such as the quality assurance techniques considered, the number of defects, the remaining defect-proneness, or product and budget data. Such knowledge is often not available. Based on a combined analysis and testing methodology called In QA, we developed an iterative rule-based procedure that considers several factors in order to gather knowledge and allows deriving different strategies to guide the quality assurance activities. We derived several specific and reasonable strategies to demonstrate the approach.