engleski

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

Background. Software engineering is in search for general principles that apply across contexts, for example, to help guiding software quality assurance. Fenton and Ohlsson presented such observations on fault distributions, which have been replicated once. Objectives. We aimed to replicate their study again to assess the robustness of the findings in a new environment, five years later. Method. We conducted a literal 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 distributions 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.

software fault distributions; software metrics; empirical research; replication

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