1st Edition

Research and Evidence in Software Engineering
From Empirical Studies to Open Source Artifacts



  • Available for pre-order. Item will ship after June 16, 2021
ISBN 9780367358525
June 16, 2021 Forthcoming by Auerbach Publications
224 Pages 62 B/W Illustrations

USD $170.00

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Book Description

Software engineering deals with the development and delivery of high-quality software to users within time and budget. New software development technologies, techniques, tools, and empirical evidence are evolving continuously as a result of ever-changing business environments. At the same time software systems and code are becoming more complex. These factors are increasing the pressure to release high quality code to diverse markets in the shortest time under high level of uncertainties.

In response to these challenging conditions, the software engineering research community is working to improve software engineering practices. Researchers are continuously publishing rigorous empirical studies, validated solutions, evaluated solutions, open source tools, experience reports and opinions that highlight innovations and advances in software engineering. Research and Evidence in Software Engineering: From Empirical Studies to Open Source Artifacts is an edited collection of chapters whose aim is to further the practice of developing and delivering high-quality software.

The book presents relevant theoretical frameworks, empirical research findings, and evaluated solutions addressing research challenges in the software engineering domain. It explores issues, techniques and practices relevant to software engineering research community. To foster collaboration among software engineering researchers, the book reports datasets related to various software engineering aspects as acquired systematically through scientific methods.

Because software is so prevalent in contemporary organizations, the book has a broad range of readers that includes:

Academics, scientists, and research who will learn about:

Latest software engineering studies and how to teach them

Innovating research lines

Formulating research proposals

Innovating techniques, tools, and practices as employed in an organizational context

New primary literature sources

Software engineers who can use the book to:

Adopt research techniques, tools, and practices in their working context

Evaluate the studies in the industrial context and adopt them to improve practice

Management executives who will find insight on:

Innovating software development strategy, practices, and policies

Incorporating interdisciplinary knowledge and practices used in other organization.

Table of Contents

1. Performance of Execution Tracing with Aspect-Oriented and Conventional Approaches
Tamas Galli, Francisco Chiclana, and Francois Siewe

2. A Survey on Software Test Specification Qualities for Legacy Software Systems
Shilpa George, Saradha Yasasvi Yeduruvada, and Dae-Kyoo Kim

3. Whom Should I Talk To? And How That Can Affect My Work!
Subhajit Datta

4. Software Project Management: Facts and Data versus Beliefs and Practice
Larry Peters

5. Inter-Parameter Dependencies in Real-World Web APIs: The IDEA Dataset
Alberto Martin-Lopez, Sergio Segura, and Antonio Ruiz-Cortés

6. Evaluating Testing Techniques in Highly Configurable Systems: The Drupal Dataset
Ana B. Sánchez, Sergio Segura and Antonio Ruiz Cortés

7. A Family of Experiments to Evaluate the Effects of Mindfulness on Software Engineering Students: The MetaMind Dataset
Beatriz Bernárdez, Margarita Cruz, Amador Durán, José A. Parejo, and Antonio Ruiz-Cortés

8. Process Performance Indicators for IT Service Management: The PPI Dataset
Bedilia Estrada-Torres, Adela del-Río-Ortega, Manuel Resinas, and Antonio Ruiz-Cortés

9. Prioritization in Automotive Software Testing: Systematic Literature Review and Directions for Future Research
Ankush Dadwal, Naohiko Tsuda, Hironori Washizaki, Yoshiaki Fukazawa, Masashi Mizoguchi, and Kentaro Yoshimura

10. Deep Embedding of Open Source Software Bug Repositories
Abeer Hamdy and Gloria Ezzat

11. Predict Who: Using NLP and Knowledge Graph Model
Tameem Ahmad, Nesar Ahmad, Mohammad Saqib, and Abu Huzaifa Khan

12. Mining Requirements and Design Documents in Software Repositories Using Natural Language Processing and Machine Learning Approaches
Ishaya Gambo, Clavers Chabi, Simon Yange, Olubukola Omodunbi, and Rhoda Ikono

13. Empirical Studies on Using Pair Programming as a Pedagogical Tool in Higher Education Courses: A Systematic Literature Review
Kuljit Kaur Chahal, Amanpreet Kaur Sidhu, Munish Saini

14. Programming Multi-Agent Coordination Using NorJADE Framework
Toufik Marir, Selma Maameri, and Rohallah Benaboud

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Editor(s)

Biography

Dr. Varun Gupta received a Ph.D. degree and Master of Technology in Computer Science and Engineering degree from Uttarakhand Technical University, India. Currently, he is a postdoctoral researcher at University of Beira Interior, Portugal.

Dr. Chetna Gupta is an Associate Professor in the Computer Science Engineering Department of Jaypee Institute of Information Technology. Noida, India. She has more than 15 years of academic experience and her research areas include software engineering, distributed software engineering, search based software engineering, risk management, and cloud computing.