Software Source Code: Statistical Modeling

Raghavendra Rao Althar; Debabrata Samanta; Debanjan Konar; Siddhartha Bhattacharyya

Published by De Gruyter 2021

Software Source Code

Statistical Modeling

Raghavendra Rao Althar , Debabrata Samanta , Debanjan Konar and Siddhartha Bhattacharyya

In the series De Gruyter STEM

https://doi.org/10.1515/9783110703399

Overview
Contents

About this book

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.

Statistic tool for the software engineer

Author / Editor information

R.Rao, First American India; D.Samanta, S.Bhattacharyya, Christ Univ., Bangalore; D.Konar, Sikkim Manipal Inst. of Technology, India.

Topics

Frontmatter Publicly Available Download PDF	I
Preface Publicly Available Download PDF	V
Contents Publicly Available Download PDF	IX
Chapter 1. Software development processes evolution Requires Authentication Unlicensed Licensed Download PDF	1
Chapter 2. A probabilistic model for fault prediction across functional and security aspects Requires Authentication Unlicensed Licensed Download PDF	25
Chapter 3. Establishing traceability between software development domain artifacts Requires Authentication Unlicensed Licensed Download PDF	61
Chapter 4. Auto code completion facilitation by structured prediction-based auto-completion model Requires Authentication Unlicensed Licensed Download PDF	103
Chapter 5. Transfer learning and one-shot learning to address software deployment issues Requires Authentication Unlicensed Licensed Download PDF	145
Chapter 6. Enabling intelligent IDEs with probabilistic models Requires Authentication Unlicensed Licensed Download PDF	179
Chapter 7. Natural language processing–based deep learning in the context of statistical modeling for software source code Requires Authentication Unlicensed Licensed Download PDF	213
Chapter 8. Impact of machine learning in cognitive computing Requires Authentication Unlicensed Licensed Download PDF	235
Chapter 9. Predicting rainfall with a regression model Requires Authentication Unlicensed Licensed Download PDF	259
Chapter 10. Understanding programming language structure at its full scale Requires Authentication Unlicensed Licensed Download PDF	283
References Requires Authentication Unlicensed Licensed Download PDF	315
Index Requires Authentication Unlicensed Licensed Download PDF	341

(Deutsch)

Language: English
Publisher: De Gruyter
Audience: Software Engineers, Programmers, Undergraduate and Graduate Students.
Pages
- Front matter: 16
- Main content: 342
Illustrations
- Illustrations: 72
- Coloured Illustrations: 48
Keywords: Softwareentwicklung; Data Mining; Statistik

eBook

Published: July 19, 2021
ISBN: 9783110703399

Paperback

Published: July 19, 2021
ISBN: 9783110703306