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Embedded Software Modeling and Design
Published in Louis Scheffer, Luciano Lavagno, Grant Martin, EDA for IC System Design, Verification, and Testing, 2018
There is a large number of specialized CASE tools for UML modeling of embedded systems. Among those, Rhapsody of I-Logix [83], Real-Time Studio of Artisan [84], TAU Generation 2 from Telelogic [76] and Rational Rose RT (now Rational Rose Technical Developer [34], which is in essence a profile implementing ROOM in the UML framework) of IBM (Rational) are probably the most common. In contrast with general-purpose UML tools, all these try to answer the designer’s need for automated support for model simulation, verification, and testing. In order to do so, they all provide an interpretation of the dynamic semantics of UML. Common features include interactive simulation of models and automatic generation of code. Nondeterminism is forbidden or eliminated by means of semantics restrictions. Some timing features and design of architecture level models are usually provided, although in nonstandard form if compared to the specifications of the SPT profile. Furthermore, the support for OCL and user-defined profiles is often quite weak.
Models and Tools for Complex Embedded Software and Systems
Published in Luciano Lavagno, Igor L. Markov, Grant Martin, Louis K. Scheffer, Electronic Design Automation for IC System Design, Verification, and Testing, 2017
There is a large number of specialized CASE tools for UML modeling of embedded systems. Among those, Rhapsody from IBM [97], Real-Time Studio from ATEGO [98], and Enterprise Architect from Sparxx [99] are probably the most common commercial solutions. However, in recent years, several open-source implementations started to appear. Among those, Topcased [100] and Papyrus [101] are probably the most popular. Both are based on the Eclipse Modeling Framework (EMF [102]) and leverage its capabilities, including the options for model transformations. In contrast with general-purpose UML tools, all these try to answer the designer’s need for automated support for model simulation, verification, and testing. In order to do so, they all provide an interpretation of the dynamic semantics of UML. Common features include interactive simulation of models and automatic generation of code. Nondeterminism is forbidden or eliminated by means of semantics restrictions. Some timing features and design of architecture-level models are usually provided, although in a nonstandard form if compared to the specifications of the MARTE profile. Furthermore, support for OCL and user-defined profiles is often quite weak.
Analysis of Ontology-Based Semantic Association Rule Mining
Published in Archana Patel, Narayan C. Debnath, Bharat Bhushan, Semantic Web Technologies, 2023
The integration of operational definitions known as semantics that are expressed as semantic web rules with a descriptive knowledge base that helps to perform decision making and enhance the knowledge base expressivity. Runumi Deve et al. (2020) formalized dengue disease for supporting clinical and diagnostic reasoning from the patient’s case sheet. The operational definitions have been incorporated with semantic web rule language to enhance the expressive capability of the dengue knowledge base [62]. Semantic ontology helps to generate domain-specific image captions for providing natural language descriptions [63]. The machine learning concepts can provide dynamic semantics to enrich concepts [64].
Reasoning about manipulation in multi-agent systems
Published in Journal of Applied Non-Classical Logics, 2022
Christopher Leturc, Grégory Bonnet
Let us notice that other works using dynamic logic to model lying or deceiving exist. For instance, Sakama (2021) recently extends his previous work (Sakama et al., 2015) and proposes to model deception with a doxastic dynamic semantics.