Titlebook: Requirements Engineering:Foundationfor Software Quality; 27th International W Fabiano Dalpiaz,Paola Spoletini Conference proceedings 2021 S

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书目名称Requirements Engineering:Foundationfor Software Quality被引频次学科排名




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书目名称Requirements Engineering:Foundationfor Software Quality年度引用学科排名




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书目名称Requirements Engineering:Foundationfor Software Quality读者反馈学科排名

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Is Requirements Similarity a Good Proxy for Software Similarity? An Empirical Investigation in Indus similar software. When a new requirement is proposed by a stakeholder, natural language processing (NLP)-based similarity metrics can be exploited to retrieve existing requirements, and in turn identify previously developed code. . Several NLP approaches for similarity computation are available, an

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Automatic Detection of Causality in Requirement Artifacts: The CiRA Approachs not only reasoning about requirements dependencies, but also various automated engineering tasks such as seamless derivation of test cases. However, causality extraction from natural language (NL) is still an open research challenge as existing approaches fail to extract causality with reasonable

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Improving Trace Link Recovery Using Semantic Relation Graphs and Spreading Activations are mainly based on algebraic Information Retrieval or machine-learning. . Machine-learning approaches usually demand reasonably large and labeled datasets to train. Algebraic Information Retrieval approaches like distance between tf-idf scores also work on smaller datasets without training but ar

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CORG: A Component-Oriented Synthetic Textual Requirements Generatorf such techniques, a large set of textual requirements with diverse structures and formats is required. However, such techniques are typically evaluated on only a few manually curated requirements that do not provide enough coverage of the targeted structures. Motivated by this problem, we introduce

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Automatically Classifying Non-functional Requirements with Feature Extraction and Supervised Machine Classification of NFRs is one way to mitigate this problem. However, because of the size and complexity of the SRS, the manual classification of NFRs is considered time-consuming, labour-intensive, and error-prone. An automated solution is needed that provides a reliable and efficient classificatio

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– A Process for Elicitation, Negotiation, and Documentation of Adaptive Requirementsronment and reacts by changing its behavior. . Representations of adaptive requirements (e.g., at runtime) and strategies for decision-making have gained a lot of interest in past and current research. Yet, there is a lack of support for . of requirements and environmental information for adaptive s

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Trustworthy AI Services in the Public Sector: What Are Citizens Saying About It?trust. . The aim of this study was to identify what kind of requirements citizens have for trustworthy AI services in the public sector. The study included 21 interviews and a design workshop of four public AI services. . The main finding was that all the participants wanted public AI services to be

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Risk-Driven Compliance Assurance for Collaborative AI Systems: A Vision Papern specific standards and regulations is a challenging research direction. This challenge is even more exacerbated for new generation of systems that leverage on machine learning components rather than deductive (top-down programmed) AI.. How can requirements engineering, together with software and s