Requirements Engineering: Foundation for Software Quality

This book constitutes the refereed proceedings of the 30th International Working Conference on Requirements Engineering: Foundation for Software Quality, REFSQ 2024, held in Winterthur, Switzerland, during April 812, 2024.
The 14 full papers and 8 short papers included in this book were carefully reviewed and selected from 59 submissions. They are organized in topical sections as follows: quality models for requirements engineering; quality requirements; explainability with and in requirements engineering; artificial intelligence for requirements engineering; natural language processing for requirements engineering; requirements engineering for artificial intelligence; crowd-based requirements engineering; and emerging topics and challenges in requirements engineering.

Inhalt
Quality models for Requirements Engineering.- How Explainable is Your System? Towards a Quality Model for Explainability.- Identifying relevant Factors of Requirements Quality: an industrial Case Study.- Quality Requirements.- Assessing the Understandability of Attack-Defense Trees for Modelling Security Requirements: an Experimental Investigation.- Learning to Rank Privacy Design Patterns: A Semantic Approach to Meeting Privacy Requirements.- A New Usability Inspection Method: Experience-based Analysis.- Governance-focused Classification of Security and Privacy Requirements from Obligations in Software Engineering Contracts.- Explainability with and in Requirements Engineering.- What Impact do my Preferences Have? A Framework for Explanation-Based Elicitation of Quality Objectives for Robotic Mission Planning.- Candidate Solutions for Defining Explainability Requirements of AI Systems.- Artificial Intelligence for Requirements Engineering.- Opportunities and Limitations of AI in Human-Centered Design - A Research Preview.- A Tertiary Study on AI for Requirements Engineering.- Exploring LLMs' ability to detect variability in requirements.- Natural Language Processing for Requirements Engineering.- Designing NLP-based solutions for requirements variability management: experiences from a design science study at Visma.- Natural2CTL: A Dataset for Natural Language Requirements and their CTL Formal Equivalents.- Requirements Engineering for Artificial Intelligence.- Towards a Comprehensive Ontology for Requirements Engineering for AI-powered Systems.- Operationalizing Machine Learning Using Requirements-Grounded MLOps.- Crowd-based Requirements Engineering.- Unveiling Competition Dynamics in Mobile App Markets through User Reviews.- Exploring the Automatic Classification of Usage Information in Feedback.- Channeling the Voice of the Crowd: Applying Structured Queries in User Feedback Collection.- Emerging Topics and Challenges in Requirements Engineering.- Requirements Information in Backlog Items: Content Analysis.- Requirements Engineering for No-Code Development (RE4NCD): A Case Study of Rapid Application Development during War.- Behavior-Driven Specification in Practice: An Experience Report.- The Return of Formal Requirements Engineering in the Era of Large Language Models.