Testing coverage based software reliability assessment incorporating effort expenditure and error generation

Kumar, Sudeep; Aggarwal, Anu G.; Gupta, Ritu

doi:10.1007/s12597-023-00680-x

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2023

DOI: 10.1007/s12597-023-00680-x

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Testing coverage based software reliability assessment incorporating effort expenditure and error generation

Sudeep Kumar

Anu G. Aggarwal

Ritu Gupta

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2024

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Cited by 2 publications

References 28 publications

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Developing an Innovative Imperfect Debugging Software Reliability Growth Model with Enhanced Testing Coverage Strategies

Nazir,

Iqbal,

Masoodi

et al. 2024

Int. J. Rel. Qual. Saf. Eng.

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In this paper, we introduce an innovative Software Reliability Growth Model (SRGM) designed to tackle the pivotal challenges associated with software reliability in the contemporary digital landscape, where the prevalence of online systems is ubiquitous. This SRGM integrates Imperfect Debugging (ID), Testing Coverage (TC), Testing Effort (TE), and error generation into a cohesive framework. Employing a sigmoid function to encapsulate TE, it incorporates three distinct TC functions: Delayed S-shaped, Exponential, and Logistic. This model relies on foundational assumptions, including the proportionality of fault detection rates to remaining faults, the introduction of new faults during debugging, and the intricate connection between fault detection and code coverage. The Mean Value Function (MVF) is computed through these differential equations, and the resultant MVFs are systematically tabulated for all models. An examination of the sigmoid TE function and the Weibull TE function across diverse datasets, utilizing a range of goodness-of-fit criteria including Mean Square Error (MSE), Pham’s Criterion (PC), Predictive Risk Ratio (PRR), Bayesian Information Criterion (BIC), and Akaike’s Information Criterion (AIC), reveals the superior performance of the sigmoid TE function over the Weibull counterpart across various datasets and evaluation criteria. In conclusion, this paper introduces a groundbreaking SRGM that seamlessly integrates ID, TC, and TE, offering valuable insights for assessing software reliability in the dynamic landscape of modern digital systems.

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Developing an Innovative Imperfect Debugging Software Reliability Growth Model with Enhanced Testing Coverage Strategies

Nazir,

Iqbal,

Masoodi

et al. 2024

Int. J. Rel. Qual. Saf. Eng.

View full text Add to dashboard Cite

show abstract

Enhancing Software Reliability Growth Modeling: Integrating Fault Severity Assessment with Multiple TEF

Kushwaha,

Kumar

2024

Int. J. Rel. Qual. Saf. Eng.

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The size and complexity of software products have expanded significantly, prompting researchers to focus on quality assessment by quantitatively assessing software product’s reliability growth. Several time dependent software reliability growth models (SRGMs) have been produced and are available in this regard. The authors evaluated errors of varied severity, but they believed that low severity faults would be repaired first, followed by high severity faults. Furthermore, the authors assumed in the change point model that the team changed their strategy, i.e., the fault detection rate changed after a particular time but making a plan and executing that strategy takes a long time, and as a result, the industry confronts a delay in software launching. As a result, two fault categories (low and high severity) are considered in this study, and two types of testing effort function (TEF) related to fault detection rate are presented to detect and fix them. Because parameters have such a large impact on model performance, their sensitivity is also investigated.

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Testing coverage based software reliability assessment incorporating effort expenditure and error generation

Cited by 2 publications

References 28 publications

Developing an Innovative Imperfect Debugging Software Reliability Growth Model with Enhanced Testing Coverage Strategies

Developing an Innovative Imperfect Debugging Software Reliability Growth Model with Enhanced Testing Coverage Strategies

Enhancing Software Reliability Growth Modeling: Integrating Fault Severity Assessment with Multiple TEF

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