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Requirements Engineering: Foundation for Software Quality : 30th International Working Conference, REFSQ 2024, Winterthur, Switzerland, April 8–11, 2024, Proceedings / edited by Daniel Mendez, Ana Moreira.

Springer Nature - Springer Computer Science eBooks 2024 English International Available online

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Format:
Book
Contributor:
Mendez, Daniel, editor.
Moreira, Ana M. D., editor.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 14588
Language:
English
Subjects (All):
Software engineering.
Education--Data processing.
Education.
Application software.
Machine learning.
Natural language processing (Computer science).
Software Engineering.
Computers and Education.
Computer and Information Systems Applications.
Machine Learning.
Natural Language Processing (NLP).
Local Subjects:
Software Engineering.
Computers and Education.
Computer and Information Systems Applications.
Machine Learning.
Natural Language Processing (NLP).
Physical Description:
1 online resource (363 pages)
Edition:
1st ed. 2024.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2024.
Summary:
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.
Contents:
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.
Notes:
Includes bibliographical references and index.
ISBN:
9783031573279
3031573277
OCLC:
1429723562

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