A survey of predicting software reliability using machine learning methods
In light of technical and technological progress, software has become an urgent need in every aspect of human life, including the medicine sector and industrial control. Therefore, it is imperative that the software always works flawlessly. The information technology sector has witnessed a rapid exp...
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| Published in | IAES international journal of artificial intelligence Vol. 13; no. 1; p. 35 |
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| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
01.03.2024
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| Online Access | Get full text |
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| Summary: | In light of technical and technological progress, software has become an urgent need in every aspect of human life, including the medicine sector and industrial control. Therefore, it is imperative that the software always works flawlessly. The information technology sector has witnessed a rapid expansion in recent years, as software companies can no longer rely only on cost advantages to stay competitive in the market, but programmers must provide reliable and high-quality software, and in order to estimate and predict software reliability using machine learning and deep learning, it was introduced A brief overview of the important scientific contributions to the subject of software reliability, and the researchers' findings of highly efficient methods and techniques for predicting software reliability. |
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| ISSN: | 2089-4872 2252-8938 |
| DOI: | 10.11591/ijai.v13.i1.pp35-44 |