Modeling Software Reliability With Power Law Testing Effort Function Under Operational Uncertain Environment

Abstract

In today's swiftly evolving technological landscape, the importance of software reliability has become crucial. To evaluate software reliability, many researchers have investigated several software reliability growth models (SRGMs). Software developers frequently use a controlled environment for software testing, where they are aware of all the factors. However, the operational environment can introduce unpredictable and unfamiliar factors. Many studies in the literature have recognized the existence of uncertainty in the operational environment with different scenarios like perfect and imperfect debugging, several testing coverage functions, different error detection rates, etc. However, the inclusion of the testing effort function (TEF) alongside this operating uncertain environment has received notably less attention. This paper addresses this gap by exploring a software reliability growth model that integrates a power law TEF to account for an operational uncertain environment. For the validation, a numerical analysis is done based on two datasets (DS1 and DS2), and the proposed model is compared to seven existing reliability models using six goodness-of-fit criteria, and other improved NCD ranking criteria. In addition, we have also conducted single and multiple-parameter sensitivity analysis, which has enabled us to identify the critical parameters. The proposed models could potentially assist system analysts in predicting various parameters related to certain software systems. The findings encourage the decision makers.