Using Historical In-Process and Product Metrics for Early Estimation of Software Failures

The benefits that a software organization obtains from estimates of product quality are dependent upon how early in the product cycle that these estimates are available. Early estimation of software quality can help organizations make informed decisions about corrective actions. To provide such early estimates we present an empirical case study of two large scale commercial operating systems, Windows XP and Windows Server 2003. In particular, we leverage various historical in-process and product metrics from Windows XP binaries to create statistical predictors to estimate the post-release failures/failure-proneness of Windows Server 2003 binaries. These models estimate the failures and failure-proneness of Windows Server 2003 binaries at statistically significant levels. Our study is unique in showing that historical predictors for a software product line can be useful, even at the very large scale of the Windows operating system