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Titlebook: Evaluation of Novel Approaches to Software Engineering; 14th International C Ernesto Damiani,George Spanoudakis,Leszek A. Macia Conference

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发表于 2025-3-21 18:11:16 | 显示全部楼层 |阅读模式
书目名称Evaluation of Novel Approaches to Software Engineering
副标题14th International C
编辑Ernesto Damiani,George Spanoudakis,Leszek A. Macia
视频video
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Evaluation of Novel Approaches to Software Engineering; 14th International C Ernesto Damiani,George Spanoudakis,Leszek A. Macia Conference
描述.This book constitutesselected, revised and extended papers of the 14th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2019, held in Heraklion, Crete, Greece, in May 2019..The 19 revised full papers presented were carefully reviewed and selected from 102 submissions. The papers included in this book contribute to the understanding of relevant trends of current research on novel approaches to software engineering for the development and maintenance of systems and applications, specically with relation to: model-driven software engineering, requirements engineering, empirical software engineering, service-oriented software engineering, business process management and engineering, knowledge management and engineering, reverse software engineering, software process improvement, software change and configuration management, software metrics, software patterns and refactoring, application integration, software architecture, cloudcomputing, and formal methods..
出版日期Conference proceedings 2020
关键词architecting; artificial intelligence; computer hardware; computer programming; computer systems; distrib
版次1
doihttps://doi.org/10.1007/978-3-030-40223-5
isbn_softcover978-3-030-40222-8
isbn_ebook978-3-030-40223-5Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Switzerland AG 2020
The information of publication is updating

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Model-Based Risk Analysis and Evaluation Using CORAS and CVSS,System using a template-based description of scenarios. In the present paper, we show how the method can be integrated into an existing risk management process like CORAS. To relate the CORAS diagrams and the template, we provide a metamodel. Our model-based approach ensures consistency and traceabi
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Evaluation of Software Product Quality Metrics,ult to implement given programming language levels of variety. This is compounded by the fact that many existing studies do not detail their methodology and tooling, which precludes researchers from creating surveys to enable data analysis on a larger scale. In our paper, we propose a comprehensive
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Model-Driven Development Applied to Mobile Health and Clinical Scores,the Ecore metamodel to describe a clinical score specification. To propose the DSML4ClinicalScores, we analyzed 89 clinical scores for defining the artifacts of this proposed Metamodel. From the concrete model created by the DSML4ClinicalScores, we apply model transformation techniques to automatica
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Model-Driven Automatic Question Generation for a Gamified Clinical Guideline Training System,rate and manage the training sessions. We employ gamification to increase user motivation and engagement in the training of guideline content. We conducted a limited formative evaluation of the prototype system and the users agreed that the system would be a useful addition to their training. Our pr
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On Improving R-TNCES Rebuilding for Reconfigurable Real-Time Systems,platform is used as a case study to demonstrate the proposed rebuilding method for real-time system models. The obtained results show the efficiency of our contribution and its scalability in large complex systems.
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Towards the Efficient Use of Dynamic Call Graph Generators of Node.js Applications,f engine-specific information is present in the call graphs and filtering can efficiently remove it. We also discuss how the asynchronous nature of JavaScript affects call graphs. Finally, we show the performance overhead of call graph generation and its side effects on module testing.
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Automated Software Measurement Strategies Elaboration Using Unsupervised Learning Data Analysis,of software measurement plans at runtime in order to have more flexible measurement processes adapted to the software needs. In this paper we aim at improving this latter. The idea is to learn from an historical measurements for generating an analysis model corresponding to the context. For that we
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