The objective of this paper is to investigate the evidence for symbolic regression using
genetic programming (GP) being an effective method for prediction and estimation in …

Software reliability models assess the reliability by predicting faults for the software.
Reliability is a real world phenomenon with many associated real-time problems. To obtain …

Software reliability growth models are nonlinear in nature, so it is difficult to estimate the
proper parameters. An estimation method based on a modified whale optimization algorithm …

In this paper, a novel reliability prediction technique based on the evidential reasoning (ER)
algorithm is developed and applied to forecast reliability in turbocharger engine systems …

When it comes to software development, precise planning, proper documentation and
proper process control, some errors are inevitable in the software environment. These …

Genetic programming (GP) models adapt better to the reliability curve when compared with
other traditional, and non-parametric models. In a previous work, we conducted experiments …

Software reliability models are used to estimate the probability that a software fails at a given
time. They are fundamental to plan test activities, and to ensure the quality of the software …

In this age of technology, building quality software is essential to competing in the business
market. One of the major principles required for any quality and business software product …

Software reliability growth modeling helps in deciding project release time and managing
project resources. A large number of such models have been presented in the past. Due to …

Traditional Software Reliability Growth Models (SRGMs) depend on unrealistic assumptions,
which makes it difficult to capture the complexities of modern software development. Recent …