A Second Replicated Quantitative Analysis of Fault Distributions in Complex Software Systems

A literal replication of Fenton and Ohlsson's study on fault distributions confirms that the uneven distribution of defects motivates uneven Distribution of quality assurance efforts, although predictors for such distribution of efforts are not sufficiently precise.

Abstract

Background. Software engineering is in search for general principles that apply across contexts, for example to help guide software quality assurance. Fenton and Ohlsson presented such observations on fault distributions, which have been replicated once. Objectives.We intend to replicate their study a second time in a new environment. Method.We conducted a close replication, collecting defect data from five consecutive releases of a large software system in the telecommunications domain, and conducted the same analysis as in the original study. Results. The replication confirms results on un-evenly distributed faults over modules, and that fault proneness distribution persist over test phases. Size measures are not useful as predictors of fault proneness, while fault densities are of the same order of magnitude across releases and contexts. Conclusions. This replication confirms that the un-even distribution of defects motivates un-even distribution of quality assurance efforts, although predictors for such distribution of efforts are not sufficiently precise.