Model transformation chains and model management for end-to-end performance decision support

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Abstract

The prototypical Model-Driven Performance Engineering (MDPE) Workbench from SAP Research permits multi-paradigm decision support for performance related questions in terms of what-if simulations, sensitivity analyses and optimizations. This support is beneficial if business analysts are designing new processes, modifying existing ones or optimizing processes. The functionality is provided as an extension of existing Process Modelling Tools, such as the tools employed by process environments like the jCOM! or the SAP NetWeaver Business Process Management (BPM) Suites as well as classical enterprise software like SAP Business Suite or Open ERP. By evaluating our workbench for real world cases we experienced that business processes may span different environments, each employing different Process Modelling Tools. The presence of heterogeneous tools influences the end-to-end performance of the overall process. Thus, the MDPE Workbench essentially needs to take the complete process into account. In this paper, a model transformation chain and a model management architecture is explained to enable such functionality. This architecture combines results from our previous publications, outlines these results in more detail and explains them in the context of end-to-end processes. Furthermore, the work is evaluated with an industrial business process which spans three different Process Modelling Tools. © 2011 Springer-Verlag.

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Fritzsche, M., & Gilani, W. (2011). Model transformation chains and model management for end-to-end performance decision support. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6491 LNCS, pp. 345–363). https://doi.org/10.1007/978-3-642-18023-1_9

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