Abstract
Many software reliability growth models based upon a non-homogeneous Poisson process (NHPP) have been proposed to measure and asses the reliability of a software system quantitatively. Generally, the error detection rate and the fault content function during software testing is considered to be dependent on the elapsed time testing. In this paper we have proposed three software reliability growth models (SRGM’s) incorporating the notion of error generation over the time as an extension of the delayed S-shaped software reliability growth model based on a non-homogeneous Poisson process (NHPP). The model parameters are estimated using the maximum likelihood method for interval domain data and three data sets are provided to illustrate the estimation technique. The proposed model is compared with the existing delayed S-shaped model based on error sum of squares, mean sum of squares, predictive ratio risk and Akaike’s information criteria using three different data sets. We show that the proposed models perform satisfactory better than the existing models.
Highlights
Over the past four decades several software models (SRGM) have been proposed by various researchers [See Pham (1993, Teng and Pham (2006), Pham (1996), Obha and Yamada (1984), Teng and Pham (2004), Zhang et al (2003)]
The pioneering attempt in the non-homogeneous Poisson process (NHPP) software reliability growth model was by Goel and Okumoto (1979) (GO)
maximum likelihood estimate (MLE) can be obtained by iterate solution procedure
Summary
Over the past four decades several software models (SRGM) have been proposed by various researchers [See Pham (1993, Teng and Pham (2006), Pham (1996), Obha and Yamada (1984), Teng and Pham (2004), Zhang et al (2003)]. Some of the important models falling under this category are due to Yamada et al (1983), Obha (1984), Bittanti et al (1988), Kapur and Garg (1992), Kapur et al (1999), Pham (2006), Chen (2010) and Lai and Garg (2012) These models were developed based on the assumption that faults detected in the testing phase are removed immediately with no debugging time delay and no new faults are introduced into the software.
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