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Fine‐Grained Software Rejuvenation Using an Extended Power‐Law NHPP Degradation Modeling.

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Title: Fine‐Grained Software Rejuvenation Using an Extended Power‐Law NHPP Degradation Modeling.
Authors: Chatterjee, Subhashis1 (AUTHOR), Nath Saren, Nripendra1 (AUTHOR) nripendra945@gmail.com, Kumar Singh, Lalit2 (AUTHOR)
Source: Software: Practice & Experience. Aug2026, Vol. 56 Issue 8, p1020-1033. 14p.
Subjects: Condition-based maintenance, Statistical models, Software maintenance, Engineering reliability theory, Poisson processes, Software reliability, Stochastic processes
Abstract: Objective: Long‐running software systems suffer from aging, characterized by rising performance degradation, resource depletion, and elevated failure rates. Conventional rejuvenation techniques, which often depend on predetermined restart intervals, model the system as simply healthy, deteriorated, or failed. However, practical evidence from a variety of fields indicates that wear and defect buildup frequently accelerate nonlinearly, necessitating more adaptable mathematical explanations. Method: Compared to simpler two‐parameter or linear models, an extended three‐parameter power‐law model which consists of a scaling factor, exponent, and offset is employed here to more accurately depict this behavior. The proposed framework enables adaptive rejuvenation policies triggered by observed conditions rather than rigid schedules by continuously monitoring a degradation metric tuned to this model. Renewal theory with rewards can be used to enhance rejuvenation timing and analytically evaluate steady‐state unavailability. Results: By accurately simulating real‐world dynamics, numerical results show that these degradation‐aware, threshold‐based policies outperform fixed interval approaches by accurately modelling real‐world dynamics, particularly in scenarios with increasing aging. Conclusions: Together, the extended degradation model and the proposed rejuvenation policies provide a unified analytical framework that improves system availability and reduces long‐run operational costs. This study shows that alert‐based strategies consistently outperform risk‐based policies because they allow for early, data‐driven maintenance across various software aging conditions. [ABSTRACT FROM AUTHOR]
Copyright of Software: Practice & Experience is the property of Wiley-Blackwell 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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DbLabel: Engineering Source
An: 195096158
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Fine‐Grained Software Rejuvenation Using an Extended Power‐Law NHPP Degradation Modeling.
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  Data: <searchLink fieldCode="AR" term="%22Chatterjee%2C+Subhashis%22">Chatterjee, Subhashis</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Nath+Saren%2C+Nripendra%22">Nath Saren, Nripendra</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> nripendra945@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Kumar+Singh%2C+Lalit%22">Kumar Singh, Lalit</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Software%3A+Practice+%26+Experience%22">Software: Practice & Experience</searchLink>. Aug2026, Vol. 56 Issue 8, p1020-1033. 14p.
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  Data: <searchLink fieldCode="DE" term="%22Condition-based+maintenance%22">Condition-based maintenance</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink><br /><searchLink fieldCode="DE" term="%22Software+maintenance%22">Software maintenance</searchLink><br /><searchLink fieldCode="DE" term="%22Engineering+reliability+theory%22">Engineering reliability theory</searchLink><br /><searchLink fieldCode="DE" term="%22Poisson+processes%22">Poisson processes</searchLink><br /><searchLink fieldCode="DE" term="%22Software+reliability%22">Software reliability</searchLink><br /><searchLink fieldCode="DE" term="%22Stochastic+processes%22">Stochastic processes</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Objective: Long‐running software systems suffer from aging, characterized by rising performance degradation, resource depletion, and elevated failure rates. Conventional rejuvenation techniques, which often depend on predetermined restart intervals, model the system as simply healthy, deteriorated, or failed. However, practical evidence from a variety of fields indicates that wear and defect buildup frequently accelerate nonlinearly, necessitating more adaptable mathematical explanations. Method: Compared to simpler two‐parameter or linear models, an extended three‐parameter power‐law model which consists of a scaling factor, exponent, and offset is employed here to more accurately depict this behavior. The proposed framework enables adaptive rejuvenation policies triggered by observed conditions rather than rigid schedules by continuously monitoring a degradation metric tuned to this model. Renewal theory with rewards can be used to enhance rejuvenation timing and analytically evaluate steady‐state unavailability. Results: By accurately simulating real‐world dynamics, numerical results show that these degradation‐aware, threshold‐based policies outperform fixed interval approaches by accurately modelling real‐world dynamics, particularly in scenarios with increasing aging. Conclusions: Together, the extended degradation model and the proposed rejuvenation policies provide a unified analytical framework that improves system availability and reduces long‐run operational costs. This study shows that alert‐based strategies consistently outperform risk‐based policies because they allow for early, data‐driven maintenance across various software aging conditions. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Software: Practice & Experience is the property of Wiley-Blackwell 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: 10.1002/spe.70075
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        Text: English
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      – SubjectFull: Software maintenance
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      – SubjectFull: Engineering reliability theory
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      – SubjectFull: Poisson processes
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      – SubjectFull: Software reliability
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              Text: Aug2026
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              Y: 2026
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