Requirements Engineering: Foundation for Software Quality 30th International Working Conference, REFSQ 2024, Winterthur, Switzerland, April 8–11, 2024, Proceedings /
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 8–12, 2024. The 14 full papers and 8 short papers included in this book were carefully r...
שמור ב:
| מחבר תאגידי: | |
|---|---|
| מחברים אחרים: | , |
| פורמט: | אלקטרוני ספר אלקטרוני |
| שפה: | אנגלית |
| יצא לאור: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| מהדורה: | 1st ed. 2024. |
| סדרה: | Lecture Notes in Computer Science,
14588 |
| נושאים: | |
| גישה מקוונת: | https://doi.org/10.1007/978-3-031-57327-9 |
| תגים: |
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| 245 | 1 | 0 | |a Requirements Engineering: Foundation for Software Quality |h [electronic resource] : |b 30th International Working Conference, REFSQ 2024, Winterthur, Switzerland, April 8–11, 2024, Proceedings / |c edited by Daniel Mendez, Ana Moreira. |
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| 505 | 0 | |a 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. | |
| 520 | |a 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 8–12, 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. | ||
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