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- W2995311856 abstract "Today, software is one of the main technologies contributing to the development of society. Therefore, its quality is a major requirement for both the global software industry and software engineering, which deals with all aspects of improving the quality and reliability of software products at all stages of their life cycle. To solve software engineering problems, the use of artificial intelligence methods is becoming increasingly relevant. The article presents a brief description of machine learning methods such as artificial neural networks, support vector machine, decision trees, inductive logic programming and others. Also, examples of the application of these methods to solve some problems of forecasting and quality assessment in software engineering are presented, recommendations for applying machine learning algorithms to solving problems of software engineering are given. The review will be useful by researchers and practitioners as a starting point, because it identifies important and promising areas of research. This will ultimately lead to more effective solving of software engineering problems, providing better, more reliable and cost effective software products. Problems in programming 2019; 4: 92-110" @default.
- W2995311856 created "2019-12-26" @default.
- W2995311856 creator A5067438228 @default.
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- W2995311856 date "2019-12-01" @default.
- W2995311856 modified "2023-09-25" @default.
- W2995311856 title "Application of machine learning in software engineering: an overview" @default.
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- W2995311856 doi "https://doi.org/10.15407/pp2019.04.092" @default.
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