Modelling software fault dependency using lag function

Abstract EN

This paper proposes a new software reliability growth model (sigma) based on the non-homogenous poison process (nhpp) that assumes the presence of two types of faults in the software namely, leading and dependent faults.

Leading faults are those that can be removed upon a failure.

But dependent faults are masked by the leading faults and can be removed only after the corresponding leading fault has been removed.

A time dependent lag function has been introduced which can account for delay in removal of dependent faults.

The proposed model has the ability to fit a variety of reliability growth curves and has been validated on actual software test data sets and its performance has been compared with well-documented srgms in the literature.

A discrete version of the proposed model has also been presented.