The Experts below are selected from a list of 614283 Experts worldwide ranked by ideXlab platform
David Raffo - One of the best experts on this subject based on the ideXlab platform.
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Empirical analysis in software Process Simulation modeling
Journal of Systems and Software, 2000Co-Authors: David Raffo, Marc I. KellnerAbstract:Abstract Software Process Simulation modeling is increasingly being used to address a variety of issues from the strategic management of software development, to supporting Process improvements, to software project management training. The scope of software Process Simulation applications ranges from narrow focused portions of the life cycle to longer-term product evolutionary models with broad organizational impacts. This paper discusses some of the important empirical issues that arise in software Process Simulation modeling. We first address issues concerning real-world data used to (1) establish input parameters to a software Process Simulation model, and (2) establish actual organizational results against which the model’s results (i.e., outputs) will be compared. On the input side, the challenges include small sample sizes, considerable variability and outliers, lack of desired data, loosely defined metrics, and so forth. On the output side, the paper addresses (1) verification and validation of the model, and (2) quantitative approaches to evaluating model outputs in support of managerial decision making including financial performance using Net Present Value (NPV), multi-criteria utility functions, and Data Envelopment Analysis (DEA). The paper focuses on the stochastic modeling using Monte Carlo Simulation. The paper is grounded in the authors’ practical application experiences, and major points are illuminated by examples drawn from that field work.
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software Process Simulation modeling why what how
Journal of Systems and Software, 1999Co-Authors: Marc I. Kellner, Raymond Madachy, David RaffoAbstract:Abstract Software Process Simulation modeling is increasingly being used to address a variety of issues from the strategic management of software development, to supporting Process improvements, to software project management training. The scope of software Process Simulation applications ranges from narrow focused portions of the life cycle to longer term product evolutionary models with broad organizational impacts. This article provides an overview of work being conducted in this field. It identifies the questions and issues that Simulation can be used to address (`why'), the scope and variables that can be usefully simulated (`what'), and the modeling approaches and techniques that can be most productively employed (`how'). It includes a summary of the papers in this special issue of the Journal of Systems and Software, which were presented at the First International Silver Falls Workshop on Software Process Simulation Modeling (ProSim'98). It also provides a framework that helps characterize work in this field, and applies this new characterization scheme to many of the articles in this special issue. This paper concludes by offering some guidance in selecting a Simulation modeling approach for practical application, and recommending some issues warranting additional research.
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Software Process Simulation Modeling (ProSim‘98): WorkshopReport
Empirical Software Engineering, 1998Co-Authors: David RaffoAbstract:Software companies are faced with constant changes and increased demands for improvements to cycle time, costs, and quality. Software Process Simulation has shown to be an effective tool to evaluate changes made to a software project or development organization and to help manage these changes. The Silver Falls Workshop on Software Process Simulation Modeling (ProSim) brings both researchers and practitioners together in order to jointly explore the benefits of, and issues involved in, Software Process Simulations. The focus of this workshop is on both the application of software Process Simulation research in addressing real-world problems, as well as advances being made which will provide the foundation for Software Process Simulation modeling in the future. This paper provides a report on the ProSim’98 workshop and a summary of the technical program.
Wil M. P. Van Der Aalst - One of the best experts on this subject based on the ideXlab platform.
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business Process Simulation for operational decision support
Business Process Management, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
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Business Process Management Workshops - Business Process Simulation for operational decision support
Business Process Management Workshops, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
Moe Thandar Wynn - One of the best experts on this subject based on the ideXlab platform.
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business Process Simulation for operational decision support
Business Process Management, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
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Business Process Management Workshops - Business Process Simulation for operational decision support
Business Process Management Workshops, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
Marc I. Kellner - One of the best experts on this subject based on the ideXlab platform.
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Empirical analysis in software Process Simulation modeling
Journal of Systems and Software, 2000Co-Authors: David Raffo, Marc I. KellnerAbstract:Abstract Software Process Simulation modeling is increasingly being used to address a variety of issues from the strategic management of software development, to supporting Process improvements, to software project management training. The scope of software Process Simulation applications ranges from narrow focused portions of the life cycle to longer-term product evolutionary models with broad organizational impacts. This paper discusses some of the important empirical issues that arise in software Process Simulation modeling. We first address issues concerning real-world data used to (1) establish input parameters to a software Process Simulation model, and (2) establish actual organizational results against which the model’s results (i.e., outputs) will be compared. On the input side, the challenges include small sample sizes, considerable variability and outliers, lack of desired data, loosely defined metrics, and so forth. On the output side, the paper addresses (1) verification and validation of the model, and (2) quantitative approaches to evaluating model outputs in support of managerial decision making including financial performance using Net Present Value (NPV), multi-criteria utility functions, and Data Envelopment Analysis (DEA). The paper focuses on the stochastic modeling using Monte Carlo Simulation. The paper is grounded in the authors’ practical application experiences, and major points are illuminated by examples drawn from that field work.
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software Process Simulation modeling why what how
Journal of Systems and Software, 1999Co-Authors: Marc I. Kellner, Raymond Madachy, David RaffoAbstract:Abstract Software Process Simulation modeling is increasingly being used to address a variety of issues from the strategic management of software development, to supporting Process improvements, to software project management training. The scope of software Process Simulation applications ranges from narrow focused portions of the life cycle to longer term product evolutionary models with broad organizational impacts. This article provides an overview of work being conducted in this field. It identifies the questions and issues that Simulation can be used to address (`why'), the scope and variables that can be usefully simulated (`what'), and the modeling approaches and techniques that can be most productively employed (`how'). It includes a summary of the papers in this special issue of the Journal of Systems and Software, which were presented at the First International Silver Falls Workshop on Software Process Simulation Modeling (ProSim'98). It also provides a framework that helps characterize work in this field, and applies this new characterization scheme to many of the articles in this special issue. This paper concludes by offering some guidance in selecting a Simulation modeling approach for practical application, and recommending some issues warranting additional research.
Marlon Dumas - One of the best experts on this subject based on the ideXlab platform.
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business Process Simulation for operational decision support
Business Process Management, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
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Business Process Management Workshops - Business Process Simulation for operational decision support
Business Process Management Workshops, 2007Co-Authors: Moe Thandar Wynn, Arthur H. M. Ter Hofstede, Colin J Fidge, Marlon Dumas, Wil M. P. Van Der AalstAbstract:Contemporary business Process Simulation environments are geared towards design-time analysis, rather than operational decision support over already deployed and running Processes. In particular, Simulation experiments in existing Process Simulation environments start from an empty execution state. We investigate the requirements for a Process Simulation environment that allows Simulation experiments to start from an intermediate execution state. We propose an architecture addressing these requirements and demonstrate it through a case study conducted using the YAWL workflow engine and CPN Simulation tools.
