This book constitutes the refereed proceedings of the 28th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2022, which was held in Aston, Birmingham, UK, during March 21-24, 2022.
The 12 full and 7 short papers presented in this volume were carefully reviewed and selected from 45 submissions. They were organized in topical sections as follows: Artificial intelligence and explainability; machine learning; natural language processing; user stories; business, markets, and industrial practice; and cognition and expression. The special theme for REFSQ 2022 was "Explainability in Requirements Engineering".
Artificial Intelligence and Explainability.- Transparency and Explainability of AI Systems: Ethical Guidelines in Practice.- Requirements Engineering for Artificial Intelligence: What is a Requirements Specification for an Artificial Intelligence.- Quo Vadis, Explainability? - A Research Roadmap for Explainability Engineering.- Machine Learning.- How Effective Is Automated Trace Link Recovery in Model-Driven Development.- A Zero-Shot Learning Approach to Classifying Requirements: Preliminary Study.- Natural Language Processing.- Abbreviation-Expansion Pair Detection for Glossary Term Extraction.- Towards Explainable Formal Methods: from LTL to Natural Language with Neural Machine Translation.- Req2Spec: Transforming Software Requirements into Formal Specifications using Natural Language Processing.- FRETting About Requirements.- User Stories.- Invest in Splitting: User Story Splitting within the Software Industry.- Guided Derivation of Conceptual Models from User Stories: A Controlled Experiment.- From User Stories to Data Flow Diagram for Privacy Awareness.- Business, Markets, and Industrial Practice.- Requirements Engineering in the Market Dialogue Phase of Public Procurement: A Case Study of an Innovation Partnership for Medical Technology.- A Business Model Construction Kit for Platform Business Models - Research Preview.- On Testing Security Requirements in Industry? -- A Survey Study.- Setting AI in context: A case study on defining the context and operational design domain for automated driving.- Cognition and Expression.- Requirements Engineering for Software-Enabled Art: Challenges and Guidelines.- A Study on the Mental Models of Users Concerning Existing Software.- Vision Video Making with Novices: A Research Preview.