05322nam a22005535i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001300172072001600185072002300201072001500224245023700239250001800476264006900494300006700563336002600630337002600656338003600682347002400718490005900742505235000801520078703151650003303938650003203971650002604003650002904029650005904058650003304117650002904150650005104179650002904230650004604259700008404305700008204389710003404471773002604505776003604531776003604567830005904603856004604662912001404708912001504722912001404737999001704751978-3-031-57327-9DE-He21320251030111753.0cr nn 008mamaa240329s2024    sz |    s    |||| 0|eng d  a97830315732799978-3-031-57327-97 a10.1007/978-3-031-57327-92doi 4aQA76.758 7aUMZ2bicssc 7aCOM0512302bisacsh 7aUMZ2thema10aRequirements Engineering: Foundation for Software Qualityh[electronic resource] :b30th International Working Conference, REFSQ 2024, Winterthur, Switzerland, April 8–11, 2024, Proceedings /cedited by Daniel Mendez, Ana Moreira.  a1st ed. 2024. 1aCham :bSpringer Nature Switzerland :bImprint: Springer,c2024.  aXVII, 356 p. 105 illus., 69 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aLecture Notes in Computer Science,x1611-3349 ;v145880 aQuality 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.  aThis 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. 0aSoftware engineering.933953 0aEducationxData processing. 0aApplication software. 0aMachine learning.955059 0aNatural language processing (Computer science).96513114aSoftware Engineering.93395324aComputers and Education.24aComputer and Information Systems Applications.24aMachine Learning.95505924aNatural Language Processing (NLP).9661641 aMendez, Daniel.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9743231 aMoreira, Ana.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt9743242 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978303157326208iPrinted edition:z9783031573286 0aLecture Notes in Computer Science,x1611-3349 ;v1458840uhttps://doi.org/10.1007/978-3-031-57327-9  aZDB-2-SCS  aZDB-2-SXCS  aZDB-2-LNC  c58784d58784