Software Quality: Future Perspectives on Software Engineering Quality

Software quality is no longer a back-office concern. As systems become more intelligent, more distributed, and more intertwined with everyday life, the methods we use to build, test, and maintain them must evolve. Software Quality: Future Perspectives on Software Engineering Quality captures a focused slice of that evolution, presenting the scientific proceedings of the 13th International Conference on Software Quality (SWQD 2021), held in Vienna.

Edited by a team of researchers and practitioners from TU Wien, Blekinge Institute of Technology, Johannes Kepler University Linz, and Software Quality Lab, this volume brings together invited keynotes, full research papers, and short position pieces that explore where software engineering quality is heading next.

What You’ll Find Inside

The guiding question of SWQD 2021 was “What’s The Next Big Thing in Software Engineering and Quality?” The contributions tackle that question through five distinct themes:

• Automation in Software Engineering – including an invited keynote on assisted requirements engineering and what remains in human hands.
• Quality Assurance for AI-Based Systems – with an overview of challenges and emerging approaches for testing and validating AI-driven software.
• Machine Learning Applications – examining code review datasets, maintainability, and how ML is reshaping development.
• Industry-Academia Collaboration – bridging the gap between research ideas and real-world quality needs.
• Experimentation in Software Engineering – evidence-driven improvement through empirical methods.

Why This Matters Now

Software teams today face faster release cycles, higher reliability expectations, and the rise of AI components that behave differently from traditional software. This volume does not pretend to have all the answers, but it surfaces the right questions and shares practical research that can help organizations adapt.

From testing autogenerated OPC UA models to modeling hidden feedback loops in machine learning systems, the papers address real concerns that software quality managers, test leads, and development teams encounter.

Who Should Read This

If you work in software quality assurance, requirements engineering, software testing, or AI system development, this ebook offers a window into active research and emerging practice. It is also suitable for graduate students and academics who want a snapshot of current discussions in software engineering quality.

Part of a Trusted Series

This book appears as volume 404 in Springer’s Lecture Notes in Business Information Processing (LNBIP) series, which ensures a rigorous peer-review process and high editorial standards. The conference’s acceptance rate of 23% for full papers reflects that rigor.

Whether you are preparing a quality strategy, evaluating AI testing tools, or simply curious about where software engineering is heading, Software Quality: Future Perspectives on Software Engineering Quality offers valuable insights from researchers and practitioners shaping the field.