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Using core ontologies for extending sensitive business process modeling with the knowledge perspective 使用核心本体通过知识透视图扩展敏感业务流程建模
Mariam Ben Hassen, Mohamed Turki, F. Gargouri
This research article presents an extension of the most suitable business process modeling formalism BPMN 2.0 for including and implementing the knowledge dimension in Sensitive Business Processes (SBPs). This extension is semantically rich and well-based on core domain ontologies. We aim at enriching the graphical representation of SBPs in order to improve the localization and the identification of crucial knowledge mobilized and created by these processes. Besides, we evaluate the relevance of the evolved extension through a real medical SBP scenario.
本文提出了最适合的业务流程建模形式化BPMN 2.0的扩展,用于在敏感业务流程(sbp)中包含和实现知识维度。这个扩展语义丰富,并且很好地基于核心领域本体。我们的目标是丰富sbp的图形表示,以改进这些过程动员和创造的关键知识的定位和识别。此外,我们通过一个真实的医疗收缩压场景来评估进化的延伸的相关性。
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引用次数: 10
An approach to formal verification of python software transactional memory python软件事务性内存的形式化验证方法
B. Kordic, M. Popovic, S. Ghilezan, I. Basicevic
Although Python is one of the most widely used programming languages, and it is a foundation for a variety of parallel and distributed computing frameworks, it still lacks an applicable and reliable software transactional memory. In this paper, we present an approach to formal verification of a Python Software Transactional Memory (PSTM) solution using UPPAAL tool. The aims are (i) to apply a formal verification process to a real STM implementation in order to derive a faithful STM model based on a PSTM design and (ii) to use developed PSTM model for automated machine-checked formal verification of core system properties such as safety and liveness using a model checker tool. Firstly, an architecture of PSTM solution is introduced. Secondly, formalization and a PSTM system model are analyzed. Finally, core PSTM system's properties are verified, namely safety, liveness, and reachability. Utilizing a UPPAAL's model checker tool it is successfully verified that the PSTM system model satisfies each of the three formerly mentioned properties.
尽管Python是使用最广泛的编程语言之一,并且它是各种并行和分布式计算框架的基础,但它仍然缺乏适用且可靠的软件事务性内存。在本文中,我们提出了一种使用UPPAAL工具对Python软件事务性内存(PSTM)解决方案进行形式化验证的方法。目标是(i)将正式验证过程应用于真实的STM实现,以便基于PSTM设计推导出忠实的STM模型;(ii)使用开发的PSTM模型,使用模型检查工具对核心系统属性(如安全性和活动性)进行自动机器检查的正式验证。首先,介绍了PSTM方案的体系结构。其次,分析了系统的形式化和系统模型。最后,验证了核心PSTM系统的安全性、活动性和可达性。利用UPPAAL的模型检查工具,成功地验证了PSTM系统模型满足前面提到的三个属性中的每一个。
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引用次数: 8
Structuring analyses of complex enterprise datasets with adaptive morphogenesis methods 基于自适应形态发生方法的复杂企业数据集结构分析
Einar Polis
The potential of the adaptive morphogenesis methods proposed by architect Christopher Alexander is yet to be fully realised in enterprise data analysis context. These could be customised to provide a suitable metaphor for organising analyses and to introduce novel analysis techniques. We propose a related framework and demonstrate its usage on a prototype. Our particular focus has been on identifying fundamental structural properties similar to those Alexander found present in living structures elsewhere. In addition to giving a justified structure to analyses and wholistically organising their artifacts, the framework might be useful in assessing existing analyses and analysis patterns
架构师Christopher Alexander提出的自适应形态发生方法的潜力尚未在企业数据分析环境中得到充分实现。这些可以定制为组织分析提供合适的比喻,并引入新的分析技术。我们提出了一个相关的框架,并演示了它在原型上的使用。我们特别关注的是识别与Alexander在其他地方的生活结构中发现的相似的基本结构特性。除了为分析提供合理的结构和整体地组织它们的工件之外,框架在评估现有的分析和分析模式方面可能是有用的
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引用次数: 0
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Proceedings of the Fifth European Conference on the Engineering of Computer-Based Systems
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