Save today: Get 40% off titles in Popular Science!

Learning and Analytics in Intelligent Systems

Automated Software Engineering: A Deep Learning-Based Approach

Authors: Satapathy, S.C., Jena, A.K., Singh, J., Bilgaiyan, S.

Free Preview
  • Offers potential deep learning concepts for handling open issues in software engineering, such as the efficiency of automated testing techniques, predictions for cost estimation, data processing, and automatic code generation
  • Presents a deep learning based approach to Automated Software Engineering
  • Provides new ideas in the field of software engineering
see more benefits

Buy this book

eBook $59.99
$109.00 (listprice)
price for USA in USD
valid through February 28, 2021
  • ISBN 978-3-030-38006-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
$149.99 (listprice)
price for USA in USD
valid through February 28, 2021
Softcover $59.99
$109.99 (listprice)
price for USA in USD
valid through February 28, 2021
About this book

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 But, with the rapid changes in software development, they often prove to be outdated or incapable of handling the software’s complexity.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


Table of contents (6 chapters)

Table of contents (6 chapters)
  • Selection of Significant Metrics for Improving the Performance of Change-Proneness Modules

    Pages 1-17

    Kumar, Lov (et al.)

  • Effort Estimation of Web Based Applications Using ERD, Use Case Point Method and Machine Learning

    Pages 19-37

    Goswami, Dhiraj Kumar (et al.)

  • Usage of Machine Learning in Software Testing

    Pages 39-54

    Mahapatra, Sumit (et al.)

  • Test Scenarios Generation Using Combined Object-Oriented Models

    Pages 55-71

    Panigrahi, Satya Sobhan (et al.)

  • A Novel Approach of Software Fault Prediction Using Deep Learning Technique

    Pages 73-91

    Ghosh, Debolina (et al.)

Buy this book

eBook $59.99
$109.00 (listprice)
price for USA in USD
valid through February 28, 2021
  • ISBN 978-3-030-38006-9
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $79.99
$149.99 (listprice)
price for USA in USD
valid through February 28, 2021
Softcover $59.99
$109.99 (listprice)
price for USA in USD
valid through February 28, 2021
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Automated Software Engineering: A Deep Learning-Based Approach
Authors
Series Title
Learning and Analytics in Intelligent Systems
Series Volume
8
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-38006-9
DOI
10.1007/978-3-030-38006-9
Hardcover ISBN
978-3-030-38005-2
Softcover ISBN
978-3-030-38008-3
Series ISSN
2662-3447
Edition Number
1
Number of Pages
XI, 118
Topics