Automated Software Engineering: A Deep Learning-Based Approach

Suresh Chandra Satapathy

ISBN 10: 3030380084 / ISBN 13: 9783030380083

Edité par Springer International Publishing Jan 2021, 2021

A propos de cet article

This item is printed on demand - it takes 3-4 days longer - Neuware -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 But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software's complexity.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. 132 pp. Englisch.

N° de réf. du vendeur 9783030380083

Détails bibliographiques

• Titre: Automated Software Engineering: A Deep Learning-Based Approach
• Éditeur: Springer International Publishing Jan 2021
• Date de parution: 2021
• Langue: anglais
• ISBN à 10 chiffres: 3030380084
• ISBN à 13 chiffres: 9783030380083
• Reliure: Taschenbuch
• État de l'article: Neu

A propos de ce titre

Synopsis

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 But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software’s complexity.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.