Software Quality: The Next Big Thing in Software Engineering and Quality: 14th International Conference on Software Quality, SWQD 2022, Vienna, ... Notes in Business Information Processing)

✍ Scribed by Daniel Mendez (editor), Manuel Wimmer (editor), Dietmar Winkler (editor), Stefan Biffl (editor), Johannes Bergsmann (editor)

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 111
• Category: Library

✦ Synopsis

This book constitutes the refereed proceedings of the 14th Software Quality Days Conference, SWQD 2022, held in Vienna, Austria, during May 17-19, 2022.

The Software Quality Days (SWQD) conference started in 2009 and has grown to the biggest conference on software quality in Europe. The program of the SWQD conference is designed to encompass a stimulating mixture of practical presentations and new research topics in scientific presentations. The guiding conference topic of the SWQD 2022 is “What's The Next Big Thing in Software Engineering and Quality?”.

The 4 full papers presented in this volume were carefully reviewed and selected from 8 submissions. The contributions were organized in two topical sections named: AI in Software Engineering; and Quality Assurance for Software-Intensive Systems. The book also contains two invited talks.

✦ Table of Contents

Message from the General Chair
Message from the Scientific Program Chairs
Organization
Contents
Invited Papers
Continuous Software Engineering in the Wild
1 Introduction
2 Continuous Software Engineering in a Nutshell
3 Challenges and Future Needs
4 Conclusions
References
Motivations for and Benefits of Adopting the Test Maturity Model integration (TMMi)
1 Introduction
2 A Brief Overview of TMMi
3 Reasons (Motivations) for Adopting TMMi
4 Benefits of Adopting TMMi
5 Conclusion
References
AI in Software Engineering
Automated Code Review Comment Classification to Improve Modern Code Reviews
1 Introduction
2 Related Work
3 CommentBERT – Classifying Code-Review Comments
3.1 Classifying Comments According to Their Focus
3.2 Training BERT for Code-Review Comments
3.3 Example of Application of the Taxonomy
4 Research Design
4.1 Research Questions
4.2 Datasets
4.3 Model Validation
5 Results
6 Discussion
7 Conclusions
References
A Preliminary Study on Using Text- and Image-Based Machine Learning to Predict Software Maintainability
1 Motivation
2 Experimental Design
2.1 Dataset
2.2 Architectures and Algorithms
2.3 Training and Evaluation
2.4 Preprocessing for Text-Based Prediction
2.5 Preprocessing for Image-Based Prediction
2.6 Experiment Execution
3 Experiment Results
3.1 Text-Based Classification
3.2 Image-Based Classification
3.3 Interpretation
4 Discussion
4.1 Threats to Validity
4.2 Future Work
5 Related Work
6 Conclusion
References
Quality Assurance for Software-Intensive Systems
Specification of Passive Test Cases Using an Improved T-EARS Language
1 Introduction
2 Background
2.1 Passive Testing
2.2 Guarded Assertions
2.3 Easy Approach to Requirements Syntax (EARS)
2.4 The Ohm Grammar Language
3 Method
4 Result: The Updated T-EARS Language
4.1 Keyword Terminals
4.2 Structural Elements
4.3 Basic Data Types
4.4 Signals Data Type
4.5 Intervals Data Type
4.6 Events Data Type
4.7 Boolean Expressions
4.8 Guarded Assertion Rules
4.9 Miscellaneous Modifiers
4.10 Timing Considerations
4.11 General Structure of a T-EARS Test Case
5 Discussion on T-EARS Improvement
6 Related Work
7 Conclusion and Future Work
References
A Quality Model and Checklists for Reviewing Automotive Test Case Specifications
1 Introduction
2 Related Work
3 Developing a Quality Model for Automotive Test Case Specifications
3.1 Application of the Goal Question Metric (GQM) Approach
3.2 Automotive Test Case Specifications Quality Model
4 Review of Automotive Test Case Specifications
5 Evaluation
6 Conclusion and Future Work
References
Author Index