Software source code : statistical modelling / Raghavendra Rao Althar [and three others].

Format:

Book

Author/Creator:

Althar, Raghavendra Rao, 1981- author.

Series:

De Gruyter STEM

Language:

English

Subjects (All):

Structural engineering.

Structural design.

Physical Description:

1 online resource (XVI, 342 p.)

Place of Publication:

Berlin ; Boston : De Gruyter, [2021]

Language Note:

In English.

Summary:

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.

Contents:

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

Notes:

Description based on print version record.

Includes bibliographical references and index.

ISBN:

3-11-070339-4

OCLC:

1262307938