A Logistic Growth Model for Software Reliability Estimation Considering Uncertain Factors

Abstract

Software reliability growth models (SRGMs) are widely used to estimate software reliability by analyzing failure dataset throughout the testing process. A large number of SRGMs have been proposed on a regular basis by researchers since the 1970s. They are represented with a set of assumptions and a set of parameters. One major problem in SRGMs is that the uncertainties surrounding the assumptions and parameters are generally not taken into account by most of them. Therefore, sometimes, the predicted reliability on testing phase significantly varies in actual operational phase. This paper presents a logistic growth model that incorporates a special parameter to consider the effects of all possible uncertainties. A systematic analysis is carried out to identify the major uncertain factors and their impacts on the fault detection rate. The applicability of the model is shown by validating it on two different real datasets that are commonly used in various studies. The comparisons with nine established models in terms of mean square error (MSE), variance, predictive-ratio risk (PRR), [Formula: see text]and AIC have been presented.

A Proposal on How to Use Software Reliability Growth Model to Build Confidence in Dashboard Testing

“…(2006), Chakravarty (2007), Shaik and Akthar (2011), Gandhi et.al. (2019, and very recently Yaghoobi (2021) as well as Haque & Ahmad (2021). Most (if not all) research we found focused on how good a model can fit in predicting the growth of the software reliability.…”

“…(1997), Satoh & Yamada (2002), Pham (2005), Rafi et.al. (2010, Zang & Pi (2018), and finally Haque & Ahmad (2021) clearly demonstrate that this model is widely researched and used.…”

Exploiting Regressive Model for Population Prediction in China

“…Triambak S. used logistic growth model to predict COVID-19 mortality [6], Asraful Haque Md. used logistic growth model to analyze software reliability under uncertain factors [7], and Abdul Latif Nurul Syaza used the logistic growth model to establish agricultural management strategies [8].…”

A Software Reliability Model Considering a Scale Parameter of the Uncertainty and a New Criterion

“…Because software is used in many different ways, its roles have become very diverse, and the environment provided to each piece of software has also become very diverse. Many studies have been conducted on SRMs that assume uncertainty in operating environments [17][18][19][20][21][22][23][24][25][26]. Here, uncertain operating environments refer to the environments used by actual consumers.…”

“…To assume uncertain operating environments, Teng and Pham [18] and Pham [19] proposed an SRM utilizing a gamma distribution, and Song et al [20] assumed the uncertain operating environments to be exponential and applied the failure detection rate function as a monotonically increasing function to present a new model for uncertain operating environments. Many researchers have proposed an SRM that considers uncertain factors [21][22][23][24]. Chang et al [25] proposed an SRM that considers testing coverage, which indicates whether sufficient tests have been performed in uncertain operating environments.…”