empirical study of a three-group software quality classification model

Maintaining superior quality and reliability of software systems is an important issue in software reliability engineering. Software quality estimation models based on software metrics provide a systematic and scientific way to detect fault-prone modules and enable us to achieve high quality in software systems by focusing on high-risk modules within limited resources and budget. In previous works, classification models for software quality usually classified modules into two groups, fault-prone or not fault-prone. This thesis presents a new technique for classifying modules into three groups, i.e., high-risk, medium-risk, and low-risk groups. This new technique calibrates three-group models according to the resources available, which makes it different from other classification techniques. The proposed three-group classification method proved to be efficient and useful for resource utilization in software quality control.