@article {149,
	title = {A BPMN extension to support discrete-event simulation for healthcare applications: an explicit representation of queues, attributes and data-driven decision points},
	journal = {Journal of the Operational Research Society},
	year = {2017},
	pages = {1-15},
	abstract = {<p>Stakeholder engagement in simulation projects is important, especially in healthcare where there is a plurality of stakeholder opinions, objectives and power. One promising approach for increasing engagement is facilitated modelling. Currently, the complexity of producing a simulation model means that the {\textquoteleft}model coding{\textquoteright} stage is performed without the involvement of stakeholders, interrupting the possibility of a fully facilitated project. Early work demonstrated that with currently available software tools we can represent a simple healthcare process using Business Process Model and Notation (BPMN) and generate a simulation model automatically. However, for more complex processes, BPMN currently has a number of limitations, namely the ability to represent queues and data-driven decision points. To address these limitations, we propose a conceptual design for an extension to BPMN (BPMN4SIM) using model-driven architecture. Application to an elderly emergency care pathway in a UK hospital shows that BPMN4SIM is able to represent a more complex business process. {\textcopyright} 2017 The Operational Research Society</p>},
	keywords = {BPMN, Business process model and notation (BPMN), Computer aided software engineering, Computer software, Conceptual design, Data driven decision, Discrete event simulation, Explicit representation, Health care, Health care application, Model driven architectures, Simulation projects, Software architecture, Software design, Stakeholder engagement},
	issn = {01605682},
	doi = {10.1057/s41274-017-0267-7},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021790477\&doi=10.1057\%2fs41274-017-0267-7\&partnerID=40\&md5=f0f30c77b3cccc771c50d7b8b6c878d4},
	author = {Onggo, B.S.S. and Proudlove, N.C. and D{\textquoteright}Ambrogio, A. and Calabrese, A. and Bisogno, S. and Levialdi Ghiron, N.}
}
@conference {Bocciarelli2013218,
	title = {4SEE: A model-driven simulation engineering framework for business process analysis in a SaaS paradigm},
	booktitle = {Simulation Series},
	volume = {45},
	number = {4},
	year = {2013},
	note = {cited By 1},
	pages = {218-225},
	abstract = {The intrinsic geographical distribution and the increasing complexity are two significant properties of modern business processes (BPs) that have not been fully addressed by existing simulation tools for BP analysis. Quantitative analysis of BPs is essential both at design time, to predict the BP quality of service (QoS), and at execution time, to dynamically reconfigure the BP and guarantee the pre-agreed QoS. In this respect, this work proposes a model-driven QoS-aware framework for simulation-based quantitative analysis of BPs. Specifically, the framework adopts a distributed simulation approach that replicates the service-oriented infrastructure of a BP into the corresponding simulation infrastructure based on the HLA-Evolved standard. The proposed framework assumes a scenario in which service providers publish a set of simulation-oriented services that can be subsequently used by interested consumers to dynamically discover and evaluate the QoS of the offered services. Key to the economical feasibility of this scenario is that a model-driven approach is used to automate the derivation of the simulation software from the BPMN (Business Process Model \& Notation) models of the actual BPs. The paper presents both the proposed model-driven framework, named 4SEE, and an example application to a BP for an e-commerce scenario.},
	keywords = {Business process analysis, Business process model, Computer simulation, Computer software, Distributed simulations, Economical feasibility, Model driven approach, Quality of service, Service-oriented infrastructures, Simulation engineering, Simulation software},
	isbn = {9781627480321},
	issn = {07359276},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84876848381\&partnerID=40\&md5=735bc33d9335c85e8f26a7d6dfe860c8},
	author = {Bocciarelli, P. and Andrea D{\textquoteright}Ambrogio and Gianni, D.}
}
@article {Gianni2011819,
	title = {A software architecture to ease the development of distributed simulation systems},
	journal = {SIMULATION},
	volume = {87},
	number = {9},
	year = {2011},
	note = {cited By 13},
	pages = {819-836},
	abstract = {The simulation of modern systems may require an amount of computational resources that might not be available on a single host. Distributed simulation (DS) provides an effective way to scale up for the increased computational requirements. However, using existing DS environments remains the main obstacle to the wide adoption of DS systems, because of their inherent complexity. This complexity can be quantitatively shown by the extra effort that the development of DS systems requires compared to the development of conventional local simulation (LS) systems. In this paper we introduce SimArch, a layered architecture that eases the development of DS systems by enabling simulation developers to effortlessly obtain a DS system or derive a DS system from the equivalent LS one. A reference model is used throughout the paper to illustrate the use of SimArch in the development of DS systems and to prove how the DS development effort is lowered down with respect to the use of a conventional DS environment. {\textcopyright} 2011, SAGE Publications. All rights reserved.},
	keywords = {Computer simulation, Computer simulation languages, Computer software, development effort, Distributed computer systems, distributed simulation, Distributed simulation environments, High level architecture, Layered architecture, Simulation language, Software architecture},
	issn = {00375497},
	doi = {10.1177/0037549711400777},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80052372123\&partnerID=40\&md5=8073e46ed4ea01775fd920be558f394c},
	author = {Gianni, D. and Andrea D{\textquoteright}Ambrogio and Iazeolla, G.}
}
@conference {Iazeolla2010252,
	title = {A distributed approach to wireless system simulation},
	booktitle = {6th Advanced International Conference on Telecommunications, AICT 2010},
	year = {2010},
	note = {cited By 4},
	pages = {252-262},
	abstract = {Many papers have been published that present simulation results for wireless systems, including WiMAX. All such papers do not deal with wireless simulation approaches, and simulation is only seen as a side-means to produce numerical results. This paper does not present simulation numerical predictions. It instead deals with new simulation approaches for wireless systems and presents simulation software technologies. From the approach point of view, the "local" versus the "distributed" simulation approach is investigated to wireless systems. From the technology point of view, two new software tools are presented, for a step forward with respect to existing tools to ease the development of distributed simulation systems. The tools consist of a new distributed simulation environment (wDSEnv) and a new distributed simulation language (wDSLang). Such tools are described and a detailed WiMAX local and distributed simulation example is developed. {\textcopyright} 2010 IEEE.},
	keywords = {Computer simulation languages, Computer software, Distributed approaches, Distributed simulation environments, Distributed simulation systems, Distributed simulations, Fuzzy control, IEEE 802.16, Interoperability, Numerical analysis, Numerical predictions, Numerical results, Simulation approach, Simulation result, Simulation software, Software tool, Wimax, WiMax wireless, Wireless simulation, Wireless systems},
	isbn = {9780769540214},
	doi = {10.1109/AICT.2010.66},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77955389670\&partnerID=40\&md5=b2c180074951949ca03eb646f638f842},
	author = {Iazeolla, G. and Pieroni, A. and Andrea D{\textquoteright}Ambrogio and Gianni, D.}
}
@conference {D{\textquoteright}Ambrogio2008460,
	title = {Distributed simulation of complex systems by use of an HLA-transparent simulation language},
	booktitle = {2008 Asia Simulation Conference - 7th International Conference on System Simulation and Scientific Computing, ICSC 2008},
	year = {2008},
	note = {cited By 5},
	pages = {460-467},
	abstract = {The continuously decreasing cost of distributed systems gives academics and industry the advantage of using larger execution platforms and of reusing locally implemented software components. This is particularly true for the simulation of complex systems where the computational resources needed considerably increase with the model resolution and with the number of simulated entities. The development of such simulation systems, however, requires extra efforts compared to the conventional local ones. Example extra efforts are learning how to use the Distributed Simulation (DS) Standard (such as HLA) and the development of extra software for the synchronization and communication between the local and distributed environment. In this paper, we address the problem of defining a simulation language that can transparently support the development distributed simulation systems, by making the use of the DS standard transparent and also reducing the amount of extra software. The HLA transparent language we introduce is named jEQN, being Java-based and dealing with Extended Queueing Networks domains. The language approach, however, can be easily extended to any other DS Standard and modelling domain. {\textcopyright} 2008 IEEE.},
	keywords = {Complex systems, Computational resources, Computer simulation languages, Computer software, Dielectric relaxation, Distributed environments, Distributed simulation systems, Distributed simulations, Distributed systems, Do-mains, Java programming language, Large scale systems, Linguistics, Model resolutions, Queueing networks, Simulation languages, Simulation systems, Software components, Standardization, Standards},
	isbn = {9781424417872},
	doi = {10.1109/ASC-ICSC.2008.4675405},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-58049176462\&partnerID=40\&md5=9610842bfbbce4f9f21f913927ec00c1},
	author = {Andrea D{\textquoteright}Ambrogio and Gianni, D. and Iazeolla, G. and Pieroni, A.}
}
@conference {D{\textquoteright}Ambrogio200575,
	title = {A model transformation framework for the automated building of performance models from UML models},
	booktitle = {Proceedings of the Fifth International Workshop on Software and Performance, WOSP{\textquoteright}05},
	year = {2005},
	note = {cited By 48},
	pages = {75-86},
	abstract = {In order to effectively validate the performance of software systems throughout their development cycle it is necessary to continuously build performance models from software models and then use the obtained models to check whether the system is being developed according to its performance requirements. The model building activity is a critical and effort-consuming activity. Several approaches have been envisaged to endow software designers with tools that automatically build ready-to-evaluate performance models from software development models. One essential requirement of such tools, often disregarded by current approaches, is a high degree of interoperability with software development tools, which has the positive effect of reducing both the level of required expertise in performance theory and the burden of learning separate tools. This paper introduces a frame-work for transforming source software models into target performance models. The transformation requires a clear understanding of the abstract syntax and semantics of both the source and target models, which is obtained by use of metamodeling techniques for defining the abstract syntax of models, the interrelationships between model elements and the model transformation rules. In the paper case, the framework is applied to the transformation of source models of UML type into target models of LQN (layered queueing network) type. The proposed approach is founded on the precepts recently introduced by model-driven development (MDA) and makes use of the set of related standards (MOF, QVT, XMI). This allows to obtain a high degree of automation, so that interoperable model transformation tools can be implemented in a timely and efficient way, leading to improvements in terms of software designers{\textquoteright} productivity and system quality. Copyright 2005 ACM.},
	keywords = {Automated model building, Computer programming languages, Computer simulation, Computer software, Interoperability, Layered queueing network (LQN), Mathematical models, Mathematical transformations, Performance models, Queueing networks, Semantics, Software engineering, Software models, Software performance},
	isbn = {1595930876; 9781595930873},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33748990901\&partnerID=40\&md5=3d70f2f5116fbd9bc73c5adb8790835c},
	author = {Andrea D{\textquoteright}Ambrogio}
}
@conference {D{\textquoteright}Ambrogio200544,
	title = {Performance model building of pervasive computing},
	booktitle = {Proceedings - 2005 Workshop on Techniques, Methodologies and Tools for Performance Evaluation of Complex Systems, FIRB-Perf 2005},
	volume = {2005},
	year = {2005},
	note = {cited By 3},
	pages = {44-53},
	abstract = {Performance model building is essential to predict the ability of an application to satisfy given levels of performance or to support the search for viable alternatives. Using automated methods of model building is becoming of increasing interest to software developers who have neither the skills nor the time to do it manually. This is particularly relevant in pervasive computing, where the large number of software and hardware components requires models of so large a size that using traditional manual methods of model building would be error prone and time consuming. This paper deals with an automated method to build performance models of pervasive computing applications, which require the integration of multiple technologies, including software layers, hardware platforms and wired/wireless networks. The considered performance models are of extended queueing network (EQN) type. The method is based on a procedure that receives as input the UML model of the application to yield as output the complete EQN model, which can then be evaluated by use of any evaluation tool. {\textcopyright} 2005 IEEE.},
	keywords = {Automation, Computer software, Distributed computer systems, Extended queuing network (EQN), Manual control, Mathematical models, Performance models, Pervasive computing, Query languages, Software engineering, Wireless networks},
	isbn = {0769524478; 9780769524474},
	doi = {10.1109/FIRB-PERF.2005.15},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846989003\&partnerID=40\&md5=3ba663ef9a7a1338b9485fda4973b320},
	author = {Andrea D{\textquoteright}Ambrogio and Iazeolla, G.}
}
@article {D{\textquoteright}Ambrogio200329,
	title = {Steps towards the automatic production of performance models of web applications},
	journal = {Computer Networks},
	volume = {41},
	number = {1},
	year = {2003},
	note = {cited By 14},
	pages = {29-39},
	abstract = {<p>The automatic production of performance models of software products can encourage software designers to include performance validation in their best practices. The incorporation of methods for automatic production can also be of interest of CASE tool vendors to improve the capabilities of their commercial software development environments. This paper deals with a method that introduces a systematic approach towards the automatic production of performance models of web applications (i.e. software applications run on web platforms). The method takes in input two sets of data, the description of the platform architecture (a general view of the system platform and a detailed view of the packet flow in the platform itself) and a set of data that describes the workload imposed on the platform by the application. The produced model is an extended queueing network ready to be used by conventional evaluation tools to derive predictions on the performance of the software applications. An example is given of the method application, in which predictions of the performance of the application are obtained versus various combinations of the processing powers of the interacting hosts. {\textcopyright} 2002 Elsevier Science B.V. All rights reserved.</p>},
	keywords = {Computer aided software engineering, Computer software, Packet networks, Performance, Performance prediction, Queueing networks, World Wide Web},
	issn = {13891286},
	doi = {10.1016/S1389-1286(02)00324-9},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0037437673\&partnerID=40\&md5=03d6a60f12ce2896f634526eeeb2605e},
	author = {Andrea D{\textquoteright}Ambrogio and Iazeolla, G.}
}
@conference {Iazeolla1995221,
	title = {Collaborative IV\&V by SPEED a tool-kit for the performance IV\&V of critical software},
	booktitle = {Proceedings of the Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises, WET ICE},
	year = {1995},
	note = {cited By 1},
	pages = {221-230},
	publisher = {IEEE, Los Alamitos, CA, United States},
	organization = {IEEE, Los Alamitos, CA, United States},
	abstract = {Software performance engineering is a software engineering methodology whose scope is continuing Performance IV\&V during life cycle. SPEED (Software PErformance Evaluation and MoDeling) is a tool-kit for software Performance IV\&V according to performance engineering criteria. It is in course of development at the Laboratory for Computer Science, and CERTIA Research Center, University of Rome at TorVergata. In its present version, it generates and evaluates the Master Model of the product, a performance analysis model that continuously evolves with the product design, and that includes the software workload model and the abstract machine model, or model of the executing environment. Conventional analytical and hybrid simulation techniques can then be applied to the MM to obtain performance predictions for the product under design. The paper gives a description of the SPEED philosophy and architecture, with an accompanying application example of DBMS performance design.},
	keywords = {Computer simulation, Computer software, Computer software selection and evaluation, Critical software, Database systems, Performance, Software engineering, Software performance evaluation and modeling, Software workload model, Systems analysis},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0029516723\&partnerID=40\&md5=0a21b948e2ba7b9d5bec357bc0477f93},
	author = {Iazeolla, Giuseppe and Mirandola, Raffaela and Andrea D{\textquoteright}Ambrogio}
}
