Exploring defect data from development and customer usage on software modules over multiple releases

Traditional defect analyses of software modules have focused on either identifying error prone modules or predicting the number of faults in a module, based on a set of module attributes such as complexity, lines of code, etc. In contrast to these metrics-based modeling studies, this paper explores the relationship of the number of faults per module to the prior history of the module. Specifically, we examine the relationship between (a) the faults discovered during development of a product release and those Escaped to the field, and (b) faults in the current release and faults ir? previous releases. Based on the actual data from four releases of a commercial application pr product consisting of several thousand modules, we show that. modules with more defects in development have a higher probability of failure in the field. there is a way to assess the relative quality of software releases without detailed information on the exact release content or code size. it is sufficient to consider just the previous release for predicting the number of defects during development or field. These results cart be used to improve the prediction of quality at the module level of future releases based on rite past history.