On the probability distribution of faults in complex software systems

ContextThere are several empirical principles related to the distribution of faults in a software system (e.g. the Pareto principle) widely applied in practice and thoroughly studied in the software engineering research providing evidence in their favor. However, the knowledge of the underlying probability distribution of faults, that would enable a systematic approach and refinement of these principles, is still quite limited.ObjectiveIn this paper we study the probability distribution of faults detected during verification in four consecutive releases of a large-scale complex software system for the telecommunication exchanges. This is the first such study analyzing closed software system, replicating two previous studies for open source software.MethodWe take into consideration the Weibull, lognormal, double Pareto, Pareto, and Yule–Simon probability distributions, and investigate how well these distributions fit our empirical fault data using the non-linear regression.ResultsThe results indicate that the double Pareto distribution is the most likely choice for the underlying probability distribution. This is not consistent with the previous studies on open source software.ConclusionThe study shows that understanding the probability distribution of faults in complex software systems is more complicated than previously thought. Comparison with previous studies shows that the fault distribution strongly depends on the environment, and only further replications would make it possible to build up a general theory for a given context.