@conference {Bocciarelli20153012,
	title = {Simulation-based performance and reliability analysis of business processes},
	booktitle = {Proceedings - Winter Simulation Conference},
	volume = {2015-January},
	year = {2015},
	note = {cited By 2},
	pages = {3012-3023},
	publisher = {Institute of Electrical and Electronics Engineers Inc.},
	organization = {Institute of Electrical and Electronics Engineers Inc.},
	abstract = {<p>The use of process modeling combined with the use of simulation-based analysis provides a valuable way to analyze business processes (BPs) and to evaluate design alternatives before committing resources and effort. The simulation-based analysis of BPs usually addresses performance in terms of efficiency, i.e., focusing on time-related properties (e.g., throughput or execution time). Differently, this paper proposes an automated method for the analysis of BPs in terms of both efficiency-related performance and reliability. In addition, the method allows business analysts to carry out a joint performance and reliability analysis by introducing a so-called performability attribute. The proposed method is illustrated by use of a running example dealing with a conventional e-commerce scenario. {\textcopyright} 2014 IEEE.</p>},
	keywords = {Automated methods, Business analysts, Business Process, Design alternatives, Joint performance, Performance and reliabilities, Process Modeling, Reliability, Reliability analysis, Simulation-based analysis},
	isbn = {9781479974863},
	issn = {08917736},
	doi = {10.1109/WSC.2014.7020140},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84940521933\&partnerID=40\&md5=04c0407c66dbcda5756df2c96a686040},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio and Giglio, A. and Paglia, E.},
	editor = {Tolk A., Diallo S.Y., Ryzhov I.O., Yilmaz L.}
}
@article {Bocciarelli2014573,
	title = {A model-driven method for enacting the design-time QoS analysis of business processes},
	journal = {Software and Systems Modeling},
	volume = {13},
	number = {2},
	year = {2014},
	note = {cited By 6},
	pages = {573-598},
	publisher = {Springer Verlag},
	abstract = {<p>Business Process Management (BPM) is a holistic approach for describing, analyzing, executing, managing, and improving large enterprise business processes. A business process can be seen as a flow of tasks that are orchestrated to accomplish well-defined goals such as goods production or services delivery. From an IT perspective, BPM is closely related to a business process automation approach carried out by use of IT standards and technologies, such as service-oriented architectures (SOAs) and Web Services. This paper specifically focuses on fully automated business processes that are defined and executed as orchestrations of software services. In a BPM context, the ability to predict at design time the business process behavior assumes a strategic relevance, both to early assess whether or not the business goals are achieved and to gain a competitive advantage. A business process is typically specified by use of Business Process Modeling Notation (BPMN), the standard language for the high-level description of business processes. Unfortunately, BPMN does not support the characterization of the business process in terms of nonfunctional or QoS properties, such as performance and reliability. To overcome such a limitation, this paper introduces Performability-enabled BPMN (PyBPMN), a lightweight BPMN extension for the specification of performance and reliability properties. PyBPMN enables the design time prediction of the business processes behavior, in terms of performance and reliability properties. Such prediction activity requires the use of models that are to be first built and then evaluated. In this respect, this work introduces a model-driven method that exploits PyBPMN to predict, at design time, the performance and the reliability of a business process, either to select the process configuration that provides the best behavior or to check if a given configuration satisfies the overall requirements. The proposed model-driven method that enacts the automated analysis of a business process behavior embraces the complete business process development cycle, from the specification phase down to the implementation phase. The paper also describes how the proposed model-driven method is implemented. The several model transformations at the core of the method have been implemented by use of QVT, and the standard language for specifying model transformations provided by OMG{\textquoteright}s MDA. The availability of such automated model transformations allows business analysts to predict the process behavior with no extra effort and without being required to own specific skills of performance or reliability theory, as shown by use of an example application. {\textcopyright} 2013 Springer-Verlag Berlin Heidelberg.</p>},
	keywords = {Administrative data processing, Automation, Availability, BPMN, Business Process, Competition, Design, Enterprise resource management, Forecasting, High level languages, Information services, LQN, Mathematical models, MDA, Performance, Quality of service, Reliability, Service oriented architecture (SOA), Software architecture, Specifications, Web services},
	issn = {16191366},
	doi = {10.1007/s10270-013-0345-5},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899754418\&partnerID=40\&md5=ac7ae348f9d39ccb87a9aedb7d7524bd},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
@conference {Bocciarelli2011160,
	title = {A BPMN extension for modeling non functional properties of business processes},
	booktitle = {Simulation Series},
	volume = {43},
	number = {1 BOOK 4},
	year = {2011},
	note = {cited By 27},
	pages = {160-168},
	abstract = {Business Process Management (BPM) is an holistic approach for describing, analyzing, executing, managing and improving large enterprise business processes, which can be seen as collections of related tasks executed to accomplish well-defined goals. This paper introduces a notation for the description of a business process in terms of both functional and non-functional properties, specifically addressing the performance and reliability characterization of a business process. In the BPM context, the Business Process Modeling Notation (BPMN) is the de-facto standard for the high-level description of business processes. Unfortunately BPMN does not support the characterization of the business process in terms of non-functional properties such as performance and reliability. To overcome such limitation, this paper introduces PyBPMN (Performability-enabled BPMN), a lightweight BPMN extension for the specification of properties that address both performance and reliability. The proposed extension is based on an approach that exploits principles and standards introduced by the Model Driven Architecture (MDA), thus obtaining significant advantages in terms of easy customization and improved automation. The paper also presents an example application of the proposed extension to show how it enables the automated transformation of a business process model into a parameterized performance model whose execution gives insights about the process behavior.},
	keywords = {Administrative data processing, BPMN, Business Process, Business process management, Business process model, Business Process Modeling Notation (BPMN), Computer simulation, Enterprise resource management, MDA, Model driven architectures, Performance and reliabilities, Reliability, Software architecture, Systems engineering},
	isbn = {9781617828386},
	issn = {07359276},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84887029950\&partnerID=40\&md5=286bf26106c501019949590c37d312e2},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
@article {Bocciarelli2011265,
	title = {A model-driven method for describing and predicting the reliability of composite services},
	journal = {Software and Systems Modeling},
	volume = {10},
	number = {2},
	year = {2011},
	note = {cited By 11},
	pages = {265-280},
	abstract = {Service-oriented computing is the prominent paradigm for viewing business processes as composed of functions provided by modular and standardized services. Web services are the building blocks for the application of service-oriented computing on the Web and provide the necessary support for the consolidation of multiple services into a single composite service corresponding to the overall process. In such a context, service providers are strategically interested in both describing the quality of service (QoS) characteristics of offered services, to better qualify their offer and gain a significant advantage in the global marketplace, and predicting the level of QoS that can be offered to service consumers when building composite web services that make use of services managed by various service providers. This paper illustrates a model-driven method to automatically describe and predict the QoS of composite web services specified by use of business process execution language (BPEL). The paper specifically addresses the reliability characteristic of the QoS. The proposed method is founded on Q-WSDL, a lightweight WSDL extension for the description of the QoS characteristics of a web service, and exploits Q-WSDL to annotate reliability data onto a BPEL-based UML model of the composite service. The UML model is then used to predict and describe the reliability of the composite web service. The proposed method is illustrated by use of an example application that deals with a composite web service for the migration of PSTN telephone numbers. {\textcopyright} 2010 Springer-Verlag.},
	keywords = {BPEL, Forecasting, Information services, Model-driven prediction, QoS, Quality of service, Reliability, Service oriented architecture (SOA), Telephone systems, UML, Unified Modeling Language, Web services, WSDL},
	issn = {16191366},
	doi = {10.1007/s10270-010-0150-3},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79955480530\&partnerID=40\&md5=1e9d768badb65996f4a07183d92b15d5},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
@article {Bocciarelli2008228,
	title = {Model-driven performability analysis of composite web services},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {5119 LNCS},
	year = {2008},
	note = {cited By 14},
	pages = {228-246},
	abstract = {Web services are the building blocks of the emerging computing paradigm based on service-oriented architectures (SOAs). A web service is a self-describing, open component that supports rapid composition of distributed applications. In a SOA context, service providers are strategically interested both to predict and describe the QoS of the offered services. This paper introduces a model-driven approach to automatically predict and describe the QoS of composite web services specified by use of the Business Process Execution Language for Web Services. The paper is founded on a lightweight QoS-oriented extension of the WSDL and specifically addresses the QoS in terms of the performability attribute, which defines a combined measure of performance and reliability. The proposed approach is illustrated by use of an example application that shows how the performability analysis may lead to predictions that do not correspond to those obtained by approaches that only consider the performance attribute. {\textcopyright} 2008 Springer-Verlag Berlin Heidelberg.},
	keywords = {Building blockes, Business process execution language for web services, Combined measure, Composite web services, Distributed applications, Emerging computing paradigm, Information services, Model driven approach, Model-driven, Model-driven development, Perform-ability, Performance, Performance attributes, Quality of service, Reliability, Service oriented architecture (SOA), Service provider, Systems analysis, Web services},
	isbn = {3540698132; 9783540698135},
	issn = {03029743},
	doi = {10.1007/978-3-540-69814-2-15},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349880842\&partnerID=40\&md5=2b62ddfcd5d7d53a52f20982c298e063},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio}
}
