Novel Software Reliability Estimate for Exponential Class Models

Abstract

Increasing usage of software in every domain has raised concern over its quality and durability. Many indicators for measuring the quality and durability of the software exist. One such indicator is the software reliability, which is a measure of the life time of the software. Estimation of software reliability enables the users of the software to decide whether or not to accept the software. Knowing the probability distribution of the failure times of the software, the reliability of the software can be estimated. Herein, software reliability models having exponential failure times have been considered. The reliability has been estimated by considering the methods of Maximum Likelihood Estimation (MLE) and Minimum Variance Unbiased Estimation (MVUE). The two estimators are combined to obtain the Improved Estimator (IM). Few data sets have been considered and the estimates have been obtained using the said three methods. The three estimators are then compared using the coefficient of variation. It is observed that the Improved Estimator possesses the least value of coefficient of variation, thus indicating that the Improved Estimator is better as compared to the other two estimators and hence provides more accurate estimate of reliability. © 2022 International Society of Science and Applied Technologies