Enterprise Architecture (EA) is a widely accepted means to ease the alignment of IS projects with enterprise-wide objectives. One central artifact of EA are EA models, which provide a holistic view on the organization and support EA's stakeholder to create added value. As EA collects its data from different sources, the data can be contradictory. This work contributes to existing research by proposing a novel approach to deal with contradictory data without solving the thereby caused conflicts. In order to achieve this objective, we refine the Predictive, Probabilistic Architecture Modeling Framework (P²AMF) introduced by Johnson et al., which already incorporates a way to represent uncertainty regarding the existence of modelled entities. To make our technique usable, we generalize P²AMF from its UML/OCL notation to a graph presentation in order to apply it to EA models notated in arbitrary notations like ArchiMate. Furthermore, we add alternative scenarios in different versions along a time series to meet the requirements of a distributed EA evolution. To show the applicability of our approach, we developed a proof of concept prototype by implementing the proposed calculations and guidelines on a Neo4j graph database. Last, we argue that our approach meets the stated requirements of a distributed EA evolution.
{"title":"A Probabilistic Enterprise Architecture Model Evolution","authors":"Simon Hacks, H. Lichter","doi":"10.1109/EDOC.2018.00017","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00017","url":null,"abstract":"Enterprise Architecture (EA) is a widely accepted means to ease the alignment of IS projects with enterprise-wide objectives. One central artifact of EA are EA models, which provide a holistic view on the organization and support EA's stakeholder to create added value. As EA collects its data from different sources, the data can be contradictory. This work contributes to existing research by proposing a novel approach to deal with contradictory data without solving the thereby caused conflicts. In order to achieve this objective, we refine the Predictive, Probabilistic Architecture Modeling Framework (P²AMF) introduced by Johnson et al., which already incorporates a way to represent uncertainty regarding the existence of modelled entities. To make our technique usable, we generalize P²AMF from its UML/OCL notation to a graph presentation in order to apply it to EA models notated in arbitrary notations like ArchiMate. Furthermore, we add alternative scenarios in different versions along a time series to meet the requirements of a distributed EA evolution. To show the applicability of our approach, we developed a proof of concept prototype by implementing the proposed calculations and guidelines on a Neo4j graph database. Last, we argue that our approach meets the stated requirements of a distributed EA evolution.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"77 1","pages":"51-57"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77299604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuning Jiang, M. Jeusfeld, Yacine Atif, Jianguo Ding, Christoffer Brax, Eva Nero
Power grids form the central critical infrastructure in all developed economies. Disruptions of power supply can cause major effects on the economy and the livelihood of citizens. At the same time, power grids are being targeted by sophisticated cyber attacks. To counter these threats, we propose a domain-specific language and a repository to represent power grids and related IT components that control the power grid. We apply our tool to a standard example used in the literature to assess its expressiveness.
{"title":"A Language and Repository for Cyber Security of Smart Grids","authors":"Yuning Jiang, M. Jeusfeld, Yacine Atif, Jianguo Ding, Christoffer Brax, Eva Nero","doi":"10.1109/EDOC.2018.00029","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00029","url":null,"abstract":"Power grids form the central critical infrastructure in all developed economies. Disruptions of power supply can cause major effects on the economy and the livelihood of citizens. At the same time, power grids are being targeted by sophisticated cyber attacks. To counter these threats, we propose a domain-specific language and a repository to represent power grids and related IT components that control the power grid. We apply our tool to a standard example used in the literature to assess its expressiveness.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"52 1","pages":"164-170"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72953508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. P. Sales, J. P. Almeida, S. Santini, F. Baião, G. Guizzardi
Risk analysis is a complex and critical activity in various contexts, ranging from strategic planning to IT systems operation. Given its complexity, several Enterprise Architecture (EA) frameworks and modeling languages have been developed to help analysts in representing and analyzing risks. Yet, the notion of risk remains overloaded and conceptually unclear in most of them. In this paper, we investigate the real-world semantics underlying risk-related constructs in one of such approaches, namely ArchiMate's Risk and Security Overlay (RSO). We perform this investigation by means of ontological analysis to reveal semantic limitations in the overlay, such as ambiguity and missing constructs. Building on the results of this analysis, we propose a well-founded redesign of the risk modeling aspects of the RSO.
{"title":"Ontological Analysis and Redesign of Risk Modeling in ArchiMate","authors":"T. P. Sales, J. P. Almeida, S. Santini, F. Baião, G. Guizzardi","doi":"10.1109/EDOC.2018.00028","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00028","url":null,"abstract":"Risk analysis is a complex and critical activity in various contexts, ranging from strategic planning to IT systems operation. Given its complexity, several Enterprise Architecture (EA) frameworks and modeling languages have been developed to help analysts in representing and analyzing risks. Yet, the notion of risk remains overloaded and conceptually unclear in most of them. In this paper, we investigate the real-world semantics underlying risk-related constructs in one of such approaches, namely ArchiMate's Risk and Security Overlay (RSO). We perform this investigation by means of ontological analysis to reveal semantic limitations in the overlay, such as ambiguity and missing constructs. Building on the results of this analysis, we propose a well-founded redesign of the risk modeling aspects of the RSO.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"199 1","pages":"154-163"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91021911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Jan Øyvind Aagedal, Equatex Joao Paulo Almeida, Federal University of Espirito Santo Ebrahim Bagheri, Ryerson University Amin Beheshti, Macquarie University Ilia Bider, Stockholm University/IbisSoft Marco Brambilla, Politecnico di Milano Ruth Breu, Research Group Quality Engineering Florian Daniel, Politecnico di Milano Chiara Di Francescomarino, Fondazione Bruno Kessler-IRST Remco Dijkman, Eindhoven University of Technology Giuseppe Di Lucca, University of Sannio Schahram Dustdar, Vienna University of Technology Ricardo A. Falbo, Federal University of Espirito Santo Zaiwen Feng, University of South Australia Luis Ferreira Pires, University of Twente Ulrik Franke, RISE SICS—Swedish Institute of Computer Science Aditya Ghose, University of Wollongong Claude Godart, Loria Aniruddha Gokhale, Vanderbilt University Guido Governatori, CSIRO Georg Grossmann, University of South Australia Giancarlo Guizzardi, Federal University of Espirito Santo Jens Gulden, University of Duisburg-Essen Armin Haller, Australian National University Jun Han, Swinburne University of Technology Maria-Eugenia Iacob, University of Twente Dimka Karastoyanova, University of Groningen Alexander Knapp, Universität Augsburg Julius Köpke, Alpen-Adria-Universität Klagenfurt Institute for Informatics Systems Vinay Kulkarni, Tata Consultancy Services Research Lea Kutvonen, University of Helsinki Lam Son Lê, HCMC Tech Henrik Leopold, Vrije Universiteit Amsterdam Frank Leymann, University of Stuttgart Peter F. Linington, University of Kent Florian Matthes, Technical University of Munich
JanØyvind Aagedal, Equatex Joao Paulo Almeida、圣(Federal University of获奖易卜拉欣Bagheri, Ryerson大学麦格理大学伊利亚阿明·贝赫什蒂Bider,斯德哥尔摩大学/ IbisSoft Brambilla马克,露丝·Breu米兰理工大学研究小组明确的质量工程弗洛里安Daniel,米兰理工大学基金会Francescomarino Bruno Kessler-IRST Remco Dijkman,朱塞佩·卢卡,埃因霍温理工大学University of Sannio Schahram Dustdar,维也纳大学(University of Technology里卡多·A . Falbo、圣(Federal University of获奖Zaiwen mil,南澳大利亚大学路易斯·费雷拉·皮雷特温特,RISE SICS杰弗里的大学—Swedish Institute of Computer Science kafila Ghose, University of Wollongong克劳德·多少,Loria Aniruddha范德比尔Gokhale,大学CSIRO Guido行长格奥尔格·格罗斯曼,南澳大利亚大学Giancarlo Guizzardi、圣(Federal University of获奖,Jens荷兰盾University of Duisburg-Essen官员勒,Jun汉族,斯温伯恩,国立大学University of Technology Maria-Eugenia Iacob, University of特温特Dimka Karastoyanova,格罗宁根大学(University of Alexander视为合法,教学ä吨奥格斯堡朱利叶斯Köpke, Alpen-Adria-Universität信息学研究所Systems Vinay Kulkarni克拉根福,塔塔咨询服务研究Lea Kutvonen, Lam Son Lê赫尔辛基大学,HCMC Tech Henrik利奥波德,阿姆斯特丹Vrije Universiteit Frank Leymann斯图加特大学彼得·林顿，肯特大学弗洛里安·马特斯，慕尼黑技术大学
{"title":"EDOC 2018 Program Committee","authors":"J. Aagedal, Equatex, J. P. Almeida","doi":"10.1109/edoc.2018.00008","DOIUrl":"https://doi.org/10.1109/edoc.2018.00008","url":null,"abstract":"Jan Øyvind Aagedal, Equatex Joao Paulo Almeida, Federal University of Espirito Santo Ebrahim Bagheri, Ryerson University Amin Beheshti, Macquarie University Ilia Bider, Stockholm University/IbisSoft Marco Brambilla, Politecnico di Milano Ruth Breu, Research Group Quality Engineering Florian Daniel, Politecnico di Milano Chiara Di Francescomarino, Fondazione Bruno Kessler-IRST Remco Dijkman, Eindhoven University of Technology Giuseppe Di Lucca, University of Sannio Schahram Dustdar, Vienna University of Technology Ricardo A. Falbo, Federal University of Espirito Santo Zaiwen Feng, University of South Australia Luis Ferreira Pires, University of Twente Ulrik Franke, RISE SICS—Swedish Institute of Computer Science Aditya Ghose, University of Wollongong Claude Godart, Loria Aniruddha Gokhale, Vanderbilt University Guido Governatori, CSIRO Georg Grossmann, University of South Australia Giancarlo Guizzardi, Federal University of Espirito Santo Jens Gulden, University of Duisburg-Essen Armin Haller, Australian National University Jun Han, Swinburne University of Technology Maria-Eugenia Iacob, University of Twente Dimka Karastoyanova, University of Groningen Alexander Knapp, Universität Augsburg Julius Köpke, Alpen-Adria-Universität Klagenfurt Institute for Informatics Systems Vinay Kulkarni, Tata Consultancy Services Research Lea Kutvonen, University of Helsinki Lam Son Lê, HCMC Tech Henrik Leopold, Vrije Universiteit Amsterdam Frank Leymann, University of Stuttgart Peter F. Linington, University of Kent Florian Matthes, Technical University of Munich","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89571222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Simulation is often used to provide quantitative predictions on the performance of business processes. However, the current available business process simulation engines only support basic resource constructs and even these are sometimes lacking. This leads to simulated performance metrics that can deviate significantly from the real process performance. This paper provides an overview of the quantitative effects of incorporating these advanced resource constructs in business process simulation. Experiments are conducted to assess whether there are significant differences between the effects of using basic resource constructs and using their advanced counterparts. The main conclusions are: that the allocation strategy deployed by the resources is of significant influence on the performance of the process; that the ability to assign resources to multiple roles has a significant influence; and that simulation replications are absolutely necessary to produce reliable simulation results. These insights can be used by researchers and practitioners to understand the validity of the results of their simulation studies and as a direction for future research.
{"title":"Quantitative Effects of Advanced Resource Constructs in Business Process Simulation","authors":"Sander P. F. Peters, R. Dijkman, P. Grefen","doi":"10.1109/EDOC.2018.00024","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00024","url":null,"abstract":"Simulation is often used to provide quantitative predictions on the performance of business processes. However, the current available business process simulation engines only support basic resource constructs and even these are sometimes lacking. This leads to simulated performance metrics that can deviate significantly from the real process performance. This paper provides an overview of the quantitative effects of incorporating these advanced resource constructs in business process simulation. Experiments are conducted to assess whether there are significant differences between the effects of using basic resource constructs and using their advanced counterparts. The main conclusions are: that the allocation strategy deployed by the resources is of significant influence on the performance of the process; that the ability to assign resources to multiple roles has a significant influence; and that simulation replications are absolutely necessary to produce reliable simulation results. These insights can be used by researchers and practitioners to understand the validity of the results of their simulation studies and as a direction for future research.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"45 1","pages":"115-122"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74669957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wenhao Li, Zaiwen Feng, W. Mayer, G. Grossmann, A. Kashefi, M. Stumptner
In the era of big data, new challenges occur in the field of data federation research. New types of data sources with new formats of data have emerged, and end users need to conduct complex search and data analytical tasks, which impose requirements such flexible data federation, customized security mechanism and high-performance processing (for example, near real time query). To address these challenges, this paper proposes a data federation platform named FEDSA and reports on an initial implementation. Distinctive features of the platform include process-driven data federation, Data Federation as a Service, a simple query language over a high-level common data model, data security protection over all federation services, query re-writing and full distribution. We demonstrate how these features address the challenges, discuss the performance of the current implementation, and outline future extensions.
大数据时代对数据联邦研究领域提出了新的挑战。新的数据源类型和新的数据格式已经出现，最终用户需要执行复杂的搜索和数据分析任务，这对灵活的数据联合、定制的安全机制和高性能的处理(例如近实时查询)提出了要求。为了应对这些挑战，本文提出了一个名为FEDSA的数据联合平台，并报告了其初步实现。该平台的显著特性包括流程驱动的数据联合、数据联合即服务(data federation as a Service)、基于高级通用数据模型的简单查询语言、所有联合服务的数据安全保护、查询重写和完整分发。我们将演示这些特性如何应对挑战，讨论当前实现的性能，并概述未来的扩展。
{"title":"FEDSA: A Data Federation Platform for Law Enforcement Management","authors":"Wenhao Li, Zaiwen Feng, W. Mayer, G. Grossmann, A. Kashefi, M. Stumptner","doi":"10.1109/EDOC.2018.00013","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00013","url":null,"abstract":"In the era of big data, new challenges occur in the field of data federation research. New types of data sources with new formats of data have emerged, and end users need to conduct complex search and data analytical tasks, which impose requirements such flexible data federation, customized security mechanism and high-performance processing (for example, near real time query). To address these challenges, this paper proposes a data federation platform named FEDSA and reports on an initial implementation. Distinctive features of the platform include process-driven data federation, Data Federation as a Service, a simple query language over a high-level common data model, data security protection over all federation services, query re-writing and full distribution. We demonstrate how these features address the challenges, discuss the performance of the current implementation, and outline future extensions.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"9 1","pages":"21-27"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80204512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rich Internet Applications refers to Web applications resembling desktop solutions with sophisticated user interactions, client-side processing, and asynchronous communications. Rich Internet applications have been evolved from traditional multi-page Web applications to single page applications which handle users' interactions without the need of full-refresh at each interaction. Although many techniques, methodologies, and technologies have been proposed in the rich Internet applications literature, the need for managing variability has not yet been conveniently addressed in this domain. According to software product lines research and practice, handling variability and commonality plays an important role in decreasing the development time and improving the quality of nal products. To this end, in this paper, we aim at employing the variability management techniques in the domain of rich Internet applications. We propose a variability modeling technique based on well-known feature modeling approach and provide a method for annotating rich Internet applications with variability and deriving final application based the given con guration. The proposed method is implemented in a tool named Varion which can be used along with existing rich Internet application tools and approaches. We applied the proposed approach on Angular, a well-known Model-View-Controller framework for developing rich Internet applications.
{"title":"Managing Product Lines Variability in Rich Internet Applications","authors":"Mohsen Asadi, M. Daliri, Navid Alipour","doi":"10.1109/EDOC.2018.00034","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00034","url":null,"abstract":"Rich Internet Applications refers to Web applications resembling desktop solutions with sophisticated user interactions, client-side processing, and asynchronous communications. Rich Internet applications have been evolved from traditional multi-page Web applications to single page applications which handle users' interactions without the need of full-refresh at each interaction. Although many techniques, methodologies, and technologies have been proposed in the rich Internet applications literature, the need for managing variability has not yet been conveniently addressed in this domain. According to software product lines research and practice, handling variability and commonality plays an important role in decreasing the development time and improving the quality of nal products. To this end, in this paper, we aim at employing the variability management techniques in the domain of rich Internet applications. We propose a variability modeling technique based on well-known feature modeling approach and provide a method for annotating rich Internet applications with variability and deriving final application based the given con guration. The proposed method is implemented in a tool named Varion which can be used along with existing rich Internet application tools and approaches. We applied the proposed approach on Angular, a well-known Model-View-Controller framework for developing rich Internet applications.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"77 1","pages":"208-217"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85264964","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Massiva Roudjane, D. Rebaine, R. Khoury, Sylvain Hallé
Information systems produce different types of event logs; in many situations, it may be desirable to look for trends inside these logs. We show how trends of various kinds can be computed over such logs in real time, using a generic framework called the trend distance workflow. Many common computations on event streams turn out to be special cases of this workflow, depending on how a handful of workflow parameters are defined. This process has been implemented and tested in a real-world event stream processing tool, called BeepBeep. Experimental results show that deviations from a reference trend can be detected in realtime for streams producing up to thousands of events per second.
{"title":"Real-Time Data Mining for Event Streams","authors":"Massiva Roudjane, D. Rebaine, R. Khoury, Sylvain Hallé","doi":"10.1109/EDOC.2018.00025","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00025","url":null,"abstract":"Information systems produce different types of event logs; in many situations, it may be desirable to look for trends inside these logs. We show how trends of various kinds can be computed over such logs in real time, using a generic framework called the trend distance workflow. Many common computations on event streams turn out to be special cases of this workflow, depending on how a handful of workflow parameters are defined. This process has been implemented and tested in a real-world event stream processing tool, called BeepBeep. Experimental results show that deviations from a reference trend can be detected in realtime for streams producing up to thousands of events per second.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"124 1","pages":"123-134"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89662159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Ritter, S. Rinderle-Ma, M. Montali, Andrey Rivkin, Aman Sinha
Enterprise Integration Patterns (EIPs) and their extensions denote the informally described building blocks of current Enterprise Application Integration (EAI) systems. Although a recent approach strives to provide an EIP formalization based on Coloured Petri Nets (CPNs), it does not completely consider EAI requirements, such as complex data, transacted resources and time. In the absence of a comprehensive formal definition, the patterns cannot be verified, and thus a formal foundation of EAI is missing. In this work, we leverage the novel db-net approach that finds a better balance between the data and process-related aspects than CPNs and we extend it according to the EAI requirements that we systematically collect on a pattern level. Then we discuss pattern realizations, and evaluate our approach for comprehensiveness, test correctness, and show its applicability.
{"title":"Formalizing Application Integration Patterns","authors":"Daniel Ritter, S. Rinderle-Ma, M. Montali, Andrey Rivkin, Aman Sinha","doi":"10.1109/EDOC.2018.00012","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00012","url":null,"abstract":"Enterprise Integration Patterns (EIPs) and their extensions denote the informally described building blocks of current Enterprise Application Integration (EAI) systems. Although a recent approach strives to provide an EIP formalization based on Coloured Petri Nets (CPNs), it does not completely consider EAI requirements, such as complex data, transacted resources and time. In the absence of a comprehensive formal definition, the patterns cannot be verified, and thus a formal foundation of EAI is missing. In this work, we leverage the novel db-net approach that finds a better balance between the data and process-related aspects than CPNs and we extend it according to the EAI requirements that we systematically collect on a pattern level. Then we discuss pattern realizations, and evaluate our approach for comprehensiveness, test correctness, and show its applicability.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"17 1","pages":"11-20"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79482749","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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