Using Learning Styles to Staff and Improve Software Inspection Team Performance

Software inspections are most widely used technique by industrial practitioners for improving software quality. While inspections are an effective verification technique, evidence suggests that overall performance of an inspection process is highly dependent on an individual inspectors' ability to detect faults. Our work leverages cognitive science research to help improve the inspection team performance. This paper presents the results from two industrial studies that evaluate the effect of cognitive learning styles (LSs) of individual inspectors on their inspection team performance. The results showed that the inspection teams formed with inspectors of diverse LSs outperformed teams with similar LSs of inspectors. These results can help software managers better staff inspectors, enabling cost savings, and improving quality.