Pub Date : 2022-01-01DOI: 10.1007/978-3-031-17604-3_9
Amolkirat Singh Mangat, S. Rinderle-Ma
{"title":"Next-Activity Prediction for Non-stationary Processes with Unseen Data Variability","authors":"Amolkirat Singh Mangat, S. Rinderle-Ma","doi":"10.1007/978-3-031-17604-3_9","DOIUrl":"https://doi.org/10.1007/978-3-031-17604-3_9","url":null,"abstract":"","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"41 1","pages":"145-161"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85751279","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}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-17604-3_14
Konrad Schneid, S. Thöne, H. Kuchen
{"title":"Semi-automated Test Migration for BPMN-Based Process-Driven Applications","authors":"Konrad Schneid, S. Thöne, H. Kuchen","doi":"10.1007/978-3-031-17604-3_14","DOIUrl":"https://doi.org/10.1007/978-3-031-17604-3_14","url":null,"abstract":"","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"157 1","pages":"237-254"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75348658","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}
Pub Date : 2022-01-01DOI: 10.1007/978-3-031-17604-3_6
Adriana Xisto, Felipe Sommer, M. Costa, José Lutiano Costa da Silva, Claudia Cappelli, Vanessa Nunes
{"title":"Interoperability of Digital Government Services: A Brazilian Reference Architecture Model to Promote Communication, Management, and Reuse of Solutions","authors":"Adriana Xisto, Felipe Sommer, M. Costa, José Lutiano Costa da Silva, Claudia Cappelli, Vanessa Nunes","doi":"10.1007/978-3-031-17604-3_6","DOIUrl":"https://doi.org/10.1007/978-3-031-17604-3_6","url":null,"abstract":"","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"124 1","pages":"91-107"},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76826416","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}
F. Corradini, A. Morichetta, A. Polini, B. Re, F. Tiezzi
The BPMN 2.0 standard is nowadays largely used to model distributed informative systems in both academic and industrial contexts. The notation makes possible to represent these systems from different perspectives. A local perspective, using collaboration diagrams, to describe the internal behaviour of each component of the systems, and a global perspective, using choreography diagrams, where the interactions between system components are highlighted without exposing their internal structure. In this paper, we propose a formal approach for checking conformance of collaborations, representing possible system implementations, with respect to choreographies, representing global constraints concerning components' interactions. In particular, we provide a direct formal operational semantics for both BPMN collaboration and choreography diagrams, and we formalise the conformance concept by means of two relations defined on top of the semantics. To support the approach into practice we have developed the C 4 tool. Its main characteristic is to make the exploited formal methods transparent to systems designers, thus fostering a wider adoption of them in the development of distributed informative systems. We illustrate the benefits of our approach by means of a simple, yet realistic, example concerning a traveling scenario.
{"title":"Collaboration vs. Choreography Conformance in BPMN 2.0: From Theory to Practice","authors":"F. Corradini, A. Morichetta, A. Polini, B. Re, F. Tiezzi","doi":"10.1109/EDOC.2018.00022","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00022","url":null,"abstract":"The BPMN 2.0 standard is nowadays largely used to model distributed informative systems in both academic and industrial contexts. The notation makes possible to represent these systems from different perspectives. A local perspective, using collaboration diagrams, to describe the internal behaviour of each component of the systems, and a global perspective, using choreography diagrams, where the interactions between system components are highlighted without exposing their internal structure. In this paper, we propose a formal approach for checking conformance of collaborations, representing possible system implementations, with respect to choreographies, representing global constraints concerning components' interactions. In particular, we provide a direct formal operational semantics for both BPMN collaboration and choreography diagrams, and we formalise the conformance concept by means of two relations defined on top of the semantics. To support the approach into practice we have developed the C 4 tool. Its main characteristic is to make the exploited formal methods transparent to systems designers, thus fostering a wider adoption of them in the development of distributed informative systems. We illustrate the benefits of our approach by means of a simple, yet realistic, example concerning a traveling scenario.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"44 1","pages":"95-104"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86843299","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}
Evellin C. S. Cardoso, Jennifer Horkoff, R. Sebastiani, J. Mylopoulos
Strategic goals and strategic planning have received much attention in Management Sciences literature since the 60s. In this work, we are interested in putting strategic planning on a formal, algorithmic footing by offering a formal reasoning technique for automatic generation and selection of strategic plans. Towards this end, in previous work [1] we have introduced the concept of strategic goals and dimensional refinement operators that define strategic goals in terms of domain dimensions from the data warehouses literature. Examples of dimensions for a strategic goal such as "Increase sales in Europe over 2 years" might include time, geography and product type. Here, we propose a formalization of strategic goals and their dimensional refinements that allows one to express a strategic goal model as a planning space that can be achieved across different dimensions. Subsequently, we use automated reasoning solvers to produce optimum strategic plans to achieve such strategic goals. Our proposal is illustrated with an example from the literature.
{"title":"Planning with Strategic Goals","authors":"Evellin C. S. Cardoso, Jennifer Horkoff, R. Sebastiani, J. Mylopoulos","doi":"10.1109/EDOC.2018.00016","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00016","url":null,"abstract":"Strategic goals and strategic planning have received much attention in Management Sciences literature since the 60s. In this work, we are interested in putting strategic planning on a formal, algorithmic footing by offering a formal reasoning technique for automatic generation and selection of strategic plans. Towards this end, in previous work [1] we have introduced the concept of strategic goals and dimensional refinement operators that define strategic goals in terms of domain dimensions from the data warehouses literature. Examples of dimensions for a strategic goal such as \"Increase sales in Europe over 2 years\" might include time, geography and product type. Here, we propose a formalization of strategic goals and their dimensional refinements that allows one to express a strategic goal model as a planning space that can be achieved across different dimensions. Subsequently, we use automated reasoning solvers to produce optimum strategic plans to achieve such strategic goals. Our proposal is illustrated with an example from the literature.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"38 1","pages":"44-50"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80678952","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}
{"title":"Message from the EDOC 2018 General Chair","authors":"Robert Lagerström","doi":"10.1109/edoc.2018.00005","DOIUrl":"https://doi.org/10.1109/edoc.2018.00005","url":null,"abstract":"","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90972032","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}
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}
Business process management (BPM) enables modeling, executing and monitoring organizational processes to achieve certain business goals. Organizations continue to strive for agility and take advantage of the digital era to bring flexibility in their processes, for example by integrating complex event processing (CEP) techniques. Event handling specifies how a process interacts with its environment and how the environmental occurrences influence the execution of the process. Though highly expressive and feature-rich languages like BPMN exist for process specification, they still lack the flexibility required for event handling in different real-life scenarios. In this work, an event handling model is proposed that take into account the possibilities of event subscription at different points in time with respect to process execution. The model is grounded formally and provides mapping to Petri Nets as implementation semantics. Further, trace analysis ensures correct execution of process behavior while maintaining the temporal dependencies intact among event subscription, event occurrence, event consumption and event unsubscription.
{"title":"A Flexible Event Handling Model for Business Process Enactment","authors":"Sankalita Mandal, M. Weske","doi":"10.1109/EDOC.2018.00019","DOIUrl":"https://doi.org/10.1109/EDOC.2018.00019","url":null,"abstract":"Business process management (BPM) enables modeling, executing and monitoring organizational processes to achieve certain business goals. Organizations continue to strive for agility and take advantage of the digital era to bring flexibility in their processes, for example by integrating complex event processing (CEP) techniques. Event handling specifies how a process interacts with its environment and how the environmental occurrences influence the execution of the process. Though highly expressive and feature-rich languages like BPMN exist for process specification, they still lack the flexibility required for event handling in different real-life scenarios. In this work, an event handling model is proposed that take into account the possibilities of event subscription at different points in time with respect to process execution. The model is grounded formally and provides mapping to Petri Nets as implementation semantics. Further, trace analysis ensures correct execution of process behavior while maintaining the temporal dependencies intact among event subscription, event occurrence, event consumption and event unsubscription.","PeriodicalId":6544,"journal":{"name":"2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)","volume":"98 1","pages":"68-74"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87877531","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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