{"title":"Incorporating human dynamics into software reliability analysis: learning, fatigue, and efficiency considerations","authors":"Umashankar Samal, Ajay Kumar","doi":"10.1007/s13198-024-02368-x","DOIUrl":null,"url":null,"abstract":"<p>In this study, we present an approach to enhance software reliability, acknowledging the evolving understanding of error dynamics within software development. While traditional models predominantly attribute errors to coding mistakes, recent insights emphasize the role of human factors such as learning processes and fatigue. Our method integrates these insights by incorporating the fatigue factor of software testers and optimizing fault removal efficiency within the debugging process. This integration leads to the formulation of more realistic software reliability growth models, characterized by S-shaped learning curves and an exponential fatigue function. We conduct a thorough analysis of the models’ quality, predictive abilities, and accuracy, evaluating them against three established fit criteria. By encompassing learning, fatigue, and fault removal efficiency within our models, we provide a comprehensive framework for understanding the dynamics of software reliability.</p>","PeriodicalId":14463,"journal":{"name":"International Journal of System Assurance Engineering and Management","volume":null,"pages":null},"PeriodicalIF":1.6000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of System Assurance Engineering and Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13198-024-02368-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
In this study, we present an approach to enhance software reliability, acknowledging the evolving understanding of error dynamics within software development. While traditional models predominantly attribute errors to coding mistakes, recent insights emphasize the role of human factors such as learning processes and fatigue. Our method integrates these insights by incorporating the fatigue factor of software testers and optimizing fault removal efficiency within the debugging process. This integration leads to the formulation of more realistic software reliability growth models, characterized by S-shaped learning curves and an exponential fatigue function. We conduct a thorough analysis of the models’ quality, predictive abilities, and accuracy, evaluating them against three established fit criteria. By encompassing learning, fatigue, and fault removal efficiency within our models, we provide a comprehensive framework for understanding the dynamics of software reliability.
在本研究中，我们提出了一种提高软件可靠性的方法，同时承认对软件开发过程中错误动态的认识在不断发展。传统模型主要将错误归咎于编码错误，而最近的研究则强调了学习过程和疲劳等人为因素的作用。我们的方法整合了这些见解，将软件测试人员的疲劳因素纳入其中，并优化了调试过程中的故障排除效率。通过这种整合，我们提出了更切合实际的软件可靠性增长模型，其特点是 S 型学习曲线和指数疲劳函数。我们对模型的质量、预测能力和准确性进行了全面分析，并根据三个既定的拟合标准对其进行了评估。通过将学习、疲劳和故障排除效率纳入模型，我们为理解软件可靠性的动态变化提供了一个全面的框架。
期刊介绍：
This Journal is established with a view to cater to increased awareness for high quality research in the seamless integration of heterogeneous technologies to formulate bankable solutions to the emergent complex engineering problems.
Assurance engineering could be thought of as relating to the provision of higher confidence in the reliable and secure implementation of a system’s critical characteristic features through the espousal of a holistic approach by using a wide variety of cross disciplinary tools and techniques. Successful realization of sustainable and dependable products, systems and services involves an extensive adoption of Reliability, Quality, Safety and Risk related procedures for achieving high assurancelevels of performance; also pivotal are the management issues related to risk and uncertainty that govern the practical constraints encountered in their deployment. It is our intention to provide a platform for the modeling and analysis of large engineering systems, among the other aforementioned allied goals of systems assurance engineering, leading to the enforcement of performance enhancement measures. Achieving a fine balance between theory and practice is the primary focus. The Journal only publishes high quality papers that have passed the rigorous peer review procedure of an archival scientific Journal. The aim is an increasing number of submissions, wide circulation and a high impact factor.
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