Solution Workflows for Model-Based Analysis of Complex Systems

Moscato, Francesco; Vittorini, Valeria; Amato, Flora; Mazzeo, Antonino; Mazzocca, Nicola

doi:10.1109/tase.2011.2161981

Cited by 22 publications

(11 citation statements)

References 30 publications

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“…oriented towards the automation of hardware/software codesign, as in the Metropolis, or to the modelling and analysis of discrete event systems, as in the Möbius approach [19]), to the composition of models and the joint usage of several modelling and analysis tools (e.g. oriented towards simulation as in Ptolemy II and ModHel'X, or oriented towards the analysis of non-functional properties as in the SIMTHESys multiformalism modelling framework [5] and OsMoSys [35,52]), to the composition of modelling languages, including techniques for merging metamodels [22,46] and translating models (e.g. in AToM3).…”

Section: The Multi-paradigm Modelling Domainmentioning

confidence: 99%

Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

et al. 2018

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Model-driven techniques can be used to automatically produce formal models from different views of a system realised by using several modelling languages and notations. Specifications are transformed into formal models so facilitating the analysis of complex system for design, validation or verification purposes. However, no single formalism suits for representing all system's views. In particular, the assessment of non-functional properties often requires integrated modelling approaches. The ultimate goal of the research work described in this paper is to develop a comprehensive, theoretical and practical framework able to support the development and the integration of new or existing model-driven approaches for the automatic generation of multi-formalism models. This paper defines the core theoretical ideas on which the framework is based and demonstrates their concrete applicability to the development of a multi-formalism approach for performability assessment.

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Section: The Multi-paradigm Modelling Domainmentioning

confidence: 99%

Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

et al. 2018

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“…As a result, huge difficulties in integrating these tools remain. Moscato et al (2012) proposed a flexible solution that enables the automated generation and analysis of multi-formalism models—part of the MBE approach. Tolio et al (2013) presented a framework for composing models and integrating the tools that generate those models.…”

Section: Related Workmentioning

confidence: 99%

A model-based approach to refine process parameters in smart manufacturing

Kim

Denno

Jones

2015

Concurrent Engineering

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This article describes a model-based approach for defining and refining process parameters in dynamically changing, smart manufacturing environments. This approach uses equation-based models to predict how part quality will respond to changes in that environment. The results from these models provide the major inputs into a process-parameteroptimization technique, which is used to set the values for various process parameters. In developing these models, we integrated various concepts from process improvement frameworks, such as Define-Measure-Analyze-Improve-Control and Monitor-Analyze-Plan-Execute-Knowledge, with techniques from model-based engineering. After describing the approach, we demonstrate its use in an additive manufacturing process example.

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“…There are several available software platforms, libraries and web services [13], which can be directly applied for information extraction tasks. Some examples are outlined in the following.…”

Section: Related Workmentioning

confidence: 99%

A Semantic Search Engine in the Cloud

Amato

Gargiulo

Mazzeo

et al. 2013

2013 Eighth International Conference on P2P, Parallel, Grid, Cloud and Internet Computing

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Due to the ease of data production within the Internet era, knowledge workers are increasingly overwhelmed by information from multiple information sources and yet still find it hard to navigate and search for accessing the specific information required for the task at hand. This implies that knowledge worker productivity is reduced and that organizations may be making decisions on the basis of incomplete knowledge. Most search engines in use today strongly rely on keywords matching and on the ability of the user in the query expression. This leads to the retrieval of a large amount of irrelevant information with a direct impact on the user that spends a lot of time in browsing the results and/or to construct more complex queries to refine the search output. To overcome this limitation semantic-based solution are increasingly adopted.In this work we propose a general architecture that implements a semantic search engine in the cloud that exploits semantic technologies to retrieve and present the right information to the user. Our search engine is aimed at providing support in the task of document composition, suggesting to the user the adequate section that could be inserted within a document.

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Solution Workflows for Model-Based Analysis of Complex Systems

Cited by 22 publications

References 30 publications

Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

Towards a model-driven engineering approach for the assessment of non-functional properties using multi-formalism

A model-based approach to refine process parameters in smart manufacturing

A Semantic Search Engine in the Cloud

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