Multi-release testing coverage-based SRGM considering error generation and change-point incorporating the random effect

Ritu Bibyan (), Sameer Anand (), Anu G. Aggarwal () and Abhishek Tandon ()
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Ritu Bibyan: University of Delhi
Sameer Anand: University of Delhi
Anu G. Aggarwal: University of Delhi
Abhishek Tandon: University of Delhi

International Journal of System Assurance Engineering and Management, 2023, vol. 14, issue 5, No 22, 1877-1887

Abstract: Abstract The most essential step during the development of the software is the testing procedure which makes the software dependable and efficient. During this procedure, the observation and rectification of the faults play a significant role in increasing the reliability of the software. Various Software Reliability growth models (SRGMs) with multiple assumptions were presented by various researchers to study the software’s reliability. It is well known that the fault observation/removal rate may get affected by irregular factors causing arbitrary effects. In this study, we aim to capture this irregular variation in fault observation/removal rate by expressing it in terms of testing coverage. The fault observation/removal process has been assumed as a stochastic process and modeled it using an Itô type of stochastic differential equation. Testing coverage enables software designers to check the software’s excellence and to see if any extra efforts are required to enhance reliability. In this paper, we have developed an SRGM based on testing coverage by introducing the concept of chang-epoint, error generation, and fault detection rate with irregular fluctuations. The error generation implies that during the testing procedure faults are not disclosed entirely and more faults get introduced. Later on, we focused on the idea of multi-release by considering four releases. We have estimated the parameters of the model by using the fault dataset for consecutive releases of Tandem Computers and validated the performance by evaluating the various goodness-of-fit criteria.

Keywords: SRGMs; Error generation; Stochastic differential equation; Testing coverage; Multi-release modeling (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s13198-023-02018-8

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