发现 BPMN 协作图的技术

IF 2 3区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING Software and Systems Modeling Pub Date : 2024-02-28 DOI:10.1007/s10270-024-01153-5
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引用次数: 0

摘要

摘要 流程挖掘领域得到了用于发现单个参与者业务流程的技术和工具的积极支持。相比之下,从多个交互参与者存储的分布式数据中发现协作模型的方法还很缺乏。在这种情况下,我们提出了一种从包含参与者交互数据的事件日志集中发现协作模型的新技术。该技术通过流程挖掘社区推出的现有算法发现每个参与者的流程。然后,它分析日志,提取信息交换信息,自动将发现的进程组合成一个协作模型,代表分布式系统的行为,并提供交互分析。该技术已在一个工具中实现,并通过在不同应用领域的多次实验进行了评估。
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A technique for discovering BPMN collaboration diagrams

Abstract

The process mining domain is actively supported by techniques and tools addressing the discovery of single-participant business processes. In contrast, approaches for discovering collaboration models out of distributed data stored by multiple interacting participants are lacking. In this context, we propose a novel technique for discovering collaboration models from sets of event logs that include data about participants’ interactions. The technique discovers each participant’s process through already available algorithms introduced by the process mining community. Then, it analyzes the logs to extract information on the exchange of messages to automatically combine the discovered processes into a collaboration model representing the distributed system’s behavior and providing analytics on the interactions. The technique has been implemented in a tool evaluated via several experiments on different application domains.

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来源期刊
Software and Systems Modeling
Software and Systems Modeling 工程技术-计算机:软件工程
CiteScore
6.00
自引率
20.00%
发文量
104
审稿时长
>12 weeks
期刊介绍: We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns: Domain-specific models and modeling standards; Model-based testing techniques; Model-based simulation techniques; Formal syntax and semantics of modeling languages such as the UML; Rigorous model-based analysis; Model composition, refinement and transformation; Software Language Engineering; Modeling Languages in Science and Engineering; Language Adaptation and Composition; Metamodeling techniques; Measuring quality of models and languages; Ontological approaches to model engineering; Generating test and code artifacts from models; Model synthesis; Methodology; Model development tool environments; Modeling Cyberphysical Systems; Data intensive modeling; Derivation of explicit models from data; Case studies and experience reports with significant modeling lessons learned; Comparative analyses of modeling languages and techniques; Scientific assessment of modeling practices
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