Machine Learning for Dynamic Software Analysis: Potentials and Limits International Dagstuhl Seminar 16172, Dagstuhl Castle, Germany, April 24-27, 2016, Revised Papers
Heftet /
2018
/ Engelsk
Product details
ISBN
9783319965611
Published
2018-07-21
Publisher
Springer International Publishing AG
Height
235 mm
Width
155 mm
Age
Research, P, 06
Language
Product language
Engelsk
Format
Product format
Heftet
Number of pages
9
Machine learning of software artefacts is an emerging area of interaction between the machine learning and software analysis communities. These require new software analysis techniques based on machine learning, such as learning-based software testing, invariant generation or code synthesis.
Read more
Written by international experts Presents the state of the art and suggests new directions and collaborations for future research Gives an overview of the machine learning techniques that can be used for software analysis
Read more
GPSR Compliance
The European Union's (EU) General Product Safety Regulation (GPSR) is a set of rules that requires consumer products to be safe and our obligations to ensure this.
If you have any concerns about our products you can contact us on ProductSafety@springernature.com.
In case Publisher is established outside the EU, the EU authorized representative is:
Springer Nature Customer Service Center GmbH
Europaplatz 3
69115 Heidelberg, Germany
ProductSafety@springernature.com
Read more
Product details
ISBN
9783319965611
Published
2018-07-21
Publisher
Springer International Publishing AG
Height
235 mm
Width
155 mm
Age
Research, P, 06
Language
Product language
Engelsk
Format
Product format
Heftet
Number of pages
9