An Ideal Software Release Policy for an Improved Software Reliability Growth Model Incorporating Imperfect Debugging with Fault Removal Efficiency and Change Point
Subhashis Chatterjee and
Ankur Shukla ()
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Subhashis Chatterjee: Department of Applied Mathematics, Indian Institute of Technology (ISM), Dhanbad, Jharkhand, 826004, India
Ankur Shukla: Department of Applied Mathematics, Indian Institute of Technology (ISM), Dhanbad, Jharkhand, 826004, India
Asia-Pacific Journal of Operational Research (APJOR), 2017, vol. 34, issue 03, 1-21
Abstract:
This paper presents a general software reliability growth model (SRGM) based on non-homogeneous Poisson process (NHPP) and optimal software release policy with cost and reliability criteria. The main motive of this study is to develop a software release time decision model considering maintenance cost and warranty cost under fuzzy environment. In previous studies, maintenance cost has been defined either in terms of warranty cost or fault debugging cost. In reality, maintenance cost includes the cost of free patches, updates, technical support and future enhancement. Also, it is possible that maintenance process causes the removal of software faults in the operational phase including the faults which occur outside the warranty period or warranty definition. In other words, warranty action may be included the maintenance action, but not the converse. Considering this fact, maintenance cost and warranty cost are defined separately in the proposed study. Initially, an SRGM has been proposed with the revised concept of imperfect debugging phenomenon considering fault removal efficiency (FRE). Furthermore, the effect of changes in various environmental factors on models parameters has been taken into account. Numerical examples based on real software failure data sets have been given to analyze the performance of the proposed models.
Keywords: Software reliability; optimal release policy; software reliability growth model; fuzzy optimization; change point (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (7)
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DOI: 10.1142/S0217595917400176
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