Affiliations: Department of Operational Research, University of Delhi, Delhi, India
Correspondence:
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Corresponding author: Sameer Anand, Department of Operational Research, University of Delhi, Delhi, India. E-mail: [email protected].
Abstract: The use of computers has been increasingly prevalent in our social lives in recent years. As a result, software engineers must create trustworthy software systems. Companies often release improved versions of the core program due to the constant demand and growing competition in the software field. A variety of growth models have been created to track and measure reliability by software managers and engineers. In the testing phase, the fault content and size of the software system increase, and consequently, the fault content found and eliminated during each debugging process decreases in comparison to the fault content present at the initial stage. In this scenario, we can consider the software fault detection process to be stochastic. The fault detection process is expressed in terms of testing coverage with random effects. In this study, we construct a testing coverage-based software model incorporating random effect with change point. We have used different testing coverage functions such as Exponential and Delayed S-shaped to study the effect of randomness. Further, multi-release planning for the proposed model has been studied and validated on the real-time failure dataset from Tandem Computers with four releases. Different performance measures and goodness-of-fit have been presented using a graphical representation.
Keywords: Software reliability growth model, testing coverage, change point, stochastic differential equation, multi-release model
