UID:
almahu_9949195708302882
Format:
1 online resource (XVI, 342 p.)
ISBN:
9783110703399
,
9783110750720
Series Statement:
De Gruyter STEM
Content:
This book will focus on utilizing statistical modelling of the software source code, in order to resolve issues associated with the software development processes. Writing and maintaining software source code is a costly business; software developers need to constantly rely on large existing code bases. Statistical modelling identifies the patterns in software artifacts and utilize them for predicting the possible issues.
Note:
Frontmatter --
,
Preface --
,
Contents --
,
Chapter 1. Software development processes evolution --
,
Chapter 2. A probabilistic model for fault prediction across functional and security aspects --
,
Chapter 3. Establishing traceability between software development domain artifacts --
,
Chapter 4. Auto code completion facilitation by structured prediction-based auto-completion model --
,
Chapter 5. Transfer learning and one-shot learning to address software deployment issues --
,
Chapter 6. Enabling intelligent IDEs with probabilistic models --
,
Chapter 7. Natural language processing-based deep learning in the context of statistical modeling for software source code --
,
Chapter 8. Impact of machine learning in cognitive computing --
,
Chapter 9. Predicting rainfall with a regression model --
,
Chapter 10. Understanding programming language structure at its full scale --
,
References --
,
Index
,
Mode of access: Internet via World Wide Web.
,
In English.
In:
DG Ebook Package English 2021, De Gruyter, 9783110750720
In:
DG Plus DeG Package 2021 Part 1, De Gruyter, 9783110750706
In:
EBOOK PACKAGE COMPLETE 2021 English, De Gruyter, 9783110754001
In:
EBOOK PACKAGE COMPLETE 2021, De Gruyter, 9783110753776
In:
EBOOK PACKAGE Engineering, Computer Sciences 2021 English, De Gruyter, 9783110754070
In:
EBOOK PACKAGE Engineering, Computer Sciences 2021, De Gruyter, 9783110753837
Additional Edition:
ISBN 9783110703535
Additional Edition:
ISBN 9783110703306
Language:
English
DOI:
10.1515/9783110703399
URL:
https://doi.org/10.1515/9783110703399
URL:
https://www.degruyter.com/isbn/9783110703399
URL:
https://doi.org/10.1515/9783110703399
URL:
https://www.degruyter.com/isbn/9783110703399
URL:
https://doi.org/10.1515/9783110703399
URL:
https://www.degruyter.com/isbn/9783110703399
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