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AMBIENTUM BIOETHICA BIOLOGIA CHEMIA DIGITALIA DRAMATICA EDUCATIO ARTIS GYMNAST. ENGINEERING EPHEMERIDES EUROPAEA GEOGRAPHIA GEOLOGIA HISTORIA HISTORIA ARTIUM INFORMATICA IURISPRUDENTIA MATHEMATICA MUSICA NEGOTIA OECONOMICA PHILOLOGIA PHILOSOPHIA PHYSICA POLITICA PSYCHOLOGIA-PAEDAGOGIA SOCIOLOGIA THEOLOGIA CATHOLICA THEOLOGIA CATHOLICA LATIN THEOLOGIA GR.-CATH. VARAD THEOLOGIA ORTHODOXA THEOLOGIA REF. TRANSYLVAN
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The STUDIA UNIVERSITATIS BABEŞ-BOLYAI issue article summary The summary of the selected article appears at the bottom of the page. In order to get back to the contents of the issue this article belongs to you have to access the link from the title. In order to see all the articles of the archive which have as author/co-author one of the authors mentioned below, you have to access the link from the author's name. |
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STUDIA INFORMATICA - Issue no. 2 / 2019 | |||||||
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PREDICTING RELIABILITY OF OBJECT-ORIENTED SYSTEMS USING A NEURAL NETWORK. Authors: ALISA BUDUR, CAMELIA ȘERBAN, ANDREEA VESCAN. |
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Abstract: DOI: 10.24193/subbi.2019.2.05 Published Online: 2019-12-30 Published Print: 2019-12-30 pp. 65-79 VIEW PDF: PDF One of the most important quality attributes of computer systems is reliability, which addresses the ability of the software to perform its required function under stated conditions for a stated period of time. The paper aim is twofold. Firstly, the proposed approach explores how to define a metric to qualify the sub-aspects comprised in ISO 25010 regarding reliability as maturity and availability. Secondly, we investigate to what extent the internal structure of the system quantified by the Chidamber and Kemerer (CK) metrics may be used to predict reliability. The approach for prediction is a feed-forward neural network with back-propagation learning. The results indicate that CK metrics are promising in predicting reliability using a neural network method. Keywords: Reliability, prediction, neural network. 2010 Mathematics Subject Classification. 68T05,68M15. |
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