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The Impact of Learning, Fatigue, and Dependent Faults on Software Reliability.

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Title: The Impact of Learning, Fatigue, and Dependent Faults on Software Reliability.
Authors: Samal, Umashankar1,2 (AUTHOR) umashankar.samal249@gmail.com, Kumar, Ajay1 (AUTHOR) ajayfma@iiitm.ac.in
Source: International Journal of Reliability, Quality & Safety Engineering. Apr2025, Vol. 32 Issue 2, p1-17. 17p.
Subjects: Software reliability, Computer software quality control, Learning curve, Fatigue (Physiology), Human error, Debugging
Abstract: Software reliability is a critical factor in ensuring the quality and dependability of software systems. Historically, software errors were primarily attributed to coding mistakes. However, recent insights have revealed that human error is a dynamic phenomenon influenced by factors such as learning processes and fatigue. This paper presents an approach that incorporates tester fatigue into the debugging process, thereby improving the development of more realistic software reliability growth models (SRGMs). The proposed approach utilizes S-shaped learning curves and an exponential fatigue function to account for the dynamic nature of human error. Additionally, interdependencies between faults are considered in the analysis. The quality, predictive capabilities, and accuracy of the proposed models are rigorously evaluated using three well-established fit criteria: mean squared error (MSE), mean absolute error (MAE), and the coefficient of determination ( R 2 ), applied to two failure datasets. By integrating the fatigue factor into the proposed models, a more comprehensive representation of software reliability dynamics is provided. This research contributes to the advancement of software reliability analysis and enhances the assessment of software system dependability. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: The Impact of Learning, Fatigue, and Dependent Faults on Software Reliability.
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  Data: <searchLink fieldCode="AR" term="%22Samal%2C+Umashankar%22">Samal, Umashankar</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> umashankar.samal249@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kumar%2C+Ajay%22">Kumar, Ajay</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ajayfma@iiitm.ac.in</i>
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  Data: <searchLink fieldCode="JN" term="%22International+Journal+of+Reliability%2C+Quality+%26+Safety+Engineering%22">International Journal of Reliability, Quality & Safety Engineering</searchLink>. Apr2025, Vol. 32 Issue 2, p1-17. 17p.
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  Data: <searchLink fieldCode="DE" term="%22Software+reliability%22">Software reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+software+quality+control%22">Computer software quality control</searchLink><br /><searchLink fieldCode="DE" term="%22Learning+curve%22">Learning curve</searchLink><br /><searchLink fieldCode="DE" term="%22Fatigue+%28Physiology%29%22">Fatigue (Physiology)</searchLink><br /><searchLink fieldCode="DE" term="%22Human+error%22">Human error</searchLink><br /><searchLink fieldCode="DE" term="%22Debugging%22">Debugging</searchLink>
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  Data: Software reliability is a critical factor in ensuring the quality and dependability of software systems. Historically, software errors were primarily attributed to coding mistakes. However, recent insights have revealed that human error is a dynamic phenomenon influenced by factors such as learning processes and fatigue. This paper presents an approach that incorporates tester fatigue into the debugging process, thereby improving the development of more realistic software reliability growth models (SRGMs). The proposed approach utilizes S-shaped learning curves and an exponential fatigue function to account for the dynamic nature of human error. Additionally, interdependencies between faults are considered in the analysis. The quality, predictive capabilities, and accuracy of the proposed models are rigorously evaluated using three well-established fit criteria: mean squared error (MSE), mean absolute error (MAE), and the coefficient of determination ( R 2 ), applied to two failure datasets. By integrating the fatigue factor into the proposed models, a more comprehensive representation of software reliability dynamics is provided. This research contributes to the advancement of software reliability analysis and enhances the assessment of software system dependability. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Reliability, Quality & Safety Engineering is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1142/S0218539324400059
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      – Code: eng
        Text: English
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        PageCount: 17
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    Subjects:
      – SubjectFull: Software reliability
        Type: general
      – SubjectFull: Computer software quality control
        Type: general
      – SubjectFull: Learning curve
        Type: general
      – SubjectFull: Fatigue (Physiology)
        Type: general
      – SubjectFull: Human error
        Type: general
      – SubjectFull: Debugging
        Type: general
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      – TitleFull: The Impact of Learning, Fatigue, and Dependent Faults on Software Reliability.
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              M: 04
              Text: Apr2025
              Type: published
              Y: 2025
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