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ITI əməkdaslarının elmi isləri Elektron kitabxana Konfranslar İnformasiya Sistemi Qəzetlər UOT 004
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 Biblioqrafik təsvir
 Bayramova , T.A. Development of a method for software reliability assessment using neural networks / T.A. Bayramova // 3rd International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN 2023), . - 2023. - N: Vol. 230. - P. 445-454.
 Annotasiya
 Software reliability growth models (SRGMs) are used to estimate future failure rates and the number of residual defects in software. SRGM helps reliability software engineers make test termination decisions. Although more than 250 traditional SRGMs have been proposed for reliability assessment, research to develop more reliable models is still ongoing. Recently, new methods based on neural networks have been developed to improve the accuracy of software reliability assessment. The article develops a neural network algorithm for assessing software reliability. To do this, factors affecting software reliability and covering its life cycle were assessed. Based on them, sets for training a three-layer neural network were created.
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