Abstract:
Software quality contains many characteristics that can be measured and estimated to reach the required quality, and it can be said that software reliability is one of the most important characteristics that can be estimated through software reliability growth models (SRGMs). These models contain parameters whose values affect the accuracy of the measured reliability, and for that, the values of these parameters are estimated in several ways, such as swarm intelligence. In this work, a suggested binding between the flower pollination algorithm and the real coded genetic algorithm (named overlapping FPA (OFGA)) was used to estimate the parameters of SRGMs, and the results showed the superiority of (OFGA) over the past binding that compared with (namely, HFPA) in parameters estimating accuracy and performance using the same dataset.
Keywords
Swarm intelligence; Software Reliability Growth Models; Real Coded Genetic Algorithm; Flower Pollination Algorithm.
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 | Marwah M.A. Dabdawb received her Bachelor degree in Software Engineering in 2008 from the University of Mosul/ Iraq. Her M.Sc. degree was from the same university in 2018. She currently works as a faculty member at Software Department, University of Mosul, Iraq. Her main research interests include Software Engineering and Artificial Intelligence. |
 | Jamal Salahaldeen Alneamy received his Ph.D. degree in Computer Science from the University of Mosul in 2006. He is working as a faculty member at the Software Dept., University of Mosul, Iraq. His current research interests include Computing in Mathematics, Natural Science, Engineering and Medicine, Artificial Intelligence, and Artificial Neural Network |