Software Quality: Future Perspectives on Software Engineering Quality

13th International Conference, SWQD 2021, Vienna, Austria, January 19¿21, 2021, Proceedings
1. Auflage 2021
ISBN: 978-3-030-65853-3
Verlag: Springer International Publishing

Buch, Englisch, Band 404, 159 Seiten, Paperback, Format (B × H): 155 mm x 235 mm, Gewicht: 271 g

Reihe: Lecture Notes in Business Information Processing

This book constitutes the refereed proceedings of the 13th Software Quality Days Conference, SWQD 2021, which was planned to be held in Vienna, Austria, during January 19–21, 2021. Due to the COVID-19 pandemic, the conference was cancelled and will be merged with SWQD 2022.

The Software Quality Days (SWQD) conference started in 2009 and has grown to the biggest conference on software quality in Europe with a strong community. 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 2021 is “Future Perspectives on Software Engineering Quality”.

The 3 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 13 submissions. The volume also contains 2 invited talks and one introductory paper for an interactive session. The contributions were organized in topical sections named: automation in software engineering; quality assurance for AI-based systems; machine learning applications; industry-academia collaboration; and experimentation in software engineering.

Zielgruppe

Research

Autoren/Hrsg.

Winkler, Dietmar

Biffl, Stefan

Bergsmann, Johannes

Mendez, Daniel

Wimmer, Manuel

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering

Inhaltsverzeichnis

Automation in Software Engineering.- Assisted Requirements Engineering - What will Remain in the Hands of the Future Requirements Engineer (Keynote).- Testing Autogenerated OPC UA NodeSet Models for Product Variants in Industry.- Quality Assurance for AI-based Systems.- Quality Assurance for AI-based Systems: Overview and Challenges (Introduction to Interactive Session).- Software Quality for AI: Where we are now.- Hidden feedback loops in machine learning systems: a simulation model and preliminary results.- The AIQ Meta-Testbed: Pragmatically Bridging Academic AI Testing and Industrial Q Needs.- Machine Learning Applications.- Improving Quality of Code Review Datasets - Token-based Feature Extraction Method.- Is Machine Learning Software Just Software: A Maintainability View.- Industry-Academia Collaboration.- Solving Problems or Enabling Problem-Solving? From Purity in Empirical Software Engineering to Effective Co-Production (Keynote).- Experimentation in Software Engineering.- An Empirical Study of User Story Quality and its Impact on Open Source Project Performance.- An Approach for Platform-Independent Online Controlled Experimentation.