Reliability and optimal release time analysis for multi up-gradation software with imperfect debugging and varied testing coverage under the effect of random field environments

Subhashis Chatterjee, Deepjyoti Saha (), Akhilesh Sharma and Yogesh Verma
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Subhashis Chatterjee: IIT(ISM) Dhanbad
Deepjyoti Saha: IIT(ISM) Dhanbad
Akhilesh Sharma: GSQAD/SRG/SAC-ISRO
Yogesh Verma: GSQAD/SRG/SAC-ISRO

Annals of Operations Research, 2022, vol. 312, issue 1, No 5, 65-85

Abstract: Abstract Due to change requests for up-gradation of adding new features, software organizations always develop new versions of the software by adding new features and improving the existing software. Various software reliability growth models have been proposed considering realistic issue which affects the reliability growth of software. Testing coverage is a crucial realistic issue that influences the fault detection and correction process. The difficulty level for removing different faults is different, same kind of testing coverage function can’t capture the fault detection process for all types of faults. Also, there exist random effects in the field environment due to the change between the testing environment and the operational environment. This randomness also affects the reliability growth of software. In this paper, a software reliability growth model has been proposed considering imperfect debugging, faults removal proportionality, two types of testing coverage function in the presence of random effect of the testing environment. Here different categories of faults have been considered. Though reliability is an important issue for software professionals, they are worried about the optimal release of software at an optimal cost. Considering the testing cost and debugging cost random, a cost model has been proposed for release time analysis.

Keywords: Software reliability; Non-homogeneous poisson process (NHPP); Random field environment (RFE); Testing coverage function; Imperfect debugging; Fault removal proportionality; Optimal release time; Mean value function (MVF) (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10479-021-04258-y

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