Open source software reliability model with nonlinear fault detection and fault introduction

Abstract

In recent years, open source software (OSS) has been widely used and developed. The reliability of OSS has also become a hot research topic. Due to the complexity, dynamics, and uncertainty of the development and testing process of OSS, it is also a difficult task to accurately evaluate the reliability of OSS. In this paper, we consider the nonlinear changes of fault detection and fault introduction in the development and testing of OSS and propose a reliability model of OSS based on the nonlinear changes of fault detection and fault introduction. Experimental results show that the proposed model is more in line with the actual changes of fault detection and fault introduction in the processes of OSS development and testing. Compared with othermodels, the proposed model has better fitting and predictive performance. We also give a simple OSS optimal release method considering the testing-effort and reliability changes in the processes of OSS development and testing. The proposed model and optimized release method can effectively assist OSS developers to evaluate software reliability and determine the optimal release time.

Applicability of Software Reliability Growth Models to Open Source Software

“…However, in the OSS context, such assumption would be unrealistic due to the influence of various factors, such as non-homogeneous groups of developers and users both of which can contribute with the bug reports during the development. Additionally, the contributors are equipped with different skills, tools and resources which may lead to potential regressions with new bugs introduced and thus a rather non-linear debugging process [18].…”

“…On the other hand, Fengzhong et al [24] argued that traditional SRGMs were largely unsuitable and proposed a new type of reliability model instead. Similarly, Wang et al [18] also proposed a new SRGM targeting the OSS projects and showed that their new model outperformed the traditional ones.…”

“…Therefore, in this paper, we demonstrate a larger-scale SRGM analysis with the help of the STRAIT tool [4] to motivate future replicability of the results and reuse of datasets in different SRGM studies. [21], WES -Weibull S-Shaped model [27], GOM -Gompertz model [28], LOG -Logistic model [29], LP -Logarithmic Poisson Execution Time model [26], MSE -mean squared error, ISS -Inflection S-Shaped model [30], PNZ -Pham-Nordmann-Zhang model [31], PZ -Pham-Zhang model [32], WM -Wang-Mi model [33], L -Li model [34], W -Wang model [18] V. EMPIRICAL EVALUATION The goal of the empirical evaluation is to Compare 9 SRGMs on 88 OSS Projects in terms of several GoF measures deriving the performance of the models in the whole dataset, in the single domains, and considering for each project the software releases.…”

New non‐homogeneous Poisson process software reliability model based on a 3‐parameter S‐shaped function

“…The parameters of the model are determined based on real data, and the parameters are substituted into a reliability formula. Many models of reliability have been introduced in the past few decades [1][2][3][4][5][6][7].…”