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商品詳細
Automated Software Engineering: A Deep Learning-Based Approach. 2020 ed.
・ISBN 978-3-030-38008-3 paper EUR 139.99
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| 著者・編者 | Satapathy, Suresh Chandra / Jena, Ajay Kumar / Singh, Jagannath / Bilgaiyan, Saurabh, |
|---|---|
| シリーズ | (Learning and Analytics in Intelligent Systems) |
| 出版社 | (Springer Nature Switzerland AG, SZ) |
| 出版年月 | 2021 |
| ページ数 | 118 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A03-1114＞ |
解説
This book discusses various open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation. Many traditional techniques are available for addressing these problems. But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software's complexity. Hence, many previously used methods are proving insufficient to solve the problems now arising in software development.
The book highlights a number of unique problems and effective solutions that reflect the state-of-the-art in software engineering. Deep learning is the latest computing technique, and is now gaining popularity in various fields of software engineering. This book explores new trends and experiments that have yielded promising solutions to current challenges in software engineering. As such, it offers a valuable reference guide for a broad audience including systems analysts, software engineers, researchers, graduate students and professors engaged in teaching software engineering.