Abstract. Simulation is widely used as a tool for analyzing business processes but is mostly focused on examining rather abstract steady-state situations. Such analyses are helpful for the initial design of a business process but are less suitable for operational decision making and continuous improvement. Here we describe a simulation system for operational decision support in the context of workflow management. To do this we exploit not only the workflow’s design, but also logged data describing the system’s observed historic behavior, and information extracted about the current state of the workflow. Making use of actual data capturing the current state and historic information allows our simulations to accurately predict potential near-future behaviors for different scenarios. The approach is supported by a practical toolset which combines and extends the workflow management system YAWL and the process mining framework ProM. Keywords: Workflow Management, Process Mining, Short-term Simulation. 1

Abstract. Enterprise architecture (EA) management forms a commonly accepted means to enhance the alignment of business and IT, and to support the managed evolution of the enterprise. One major challenge of EA management is to provide decision support by analyzing as-is states of the architecture as well as assessing planned future states. Thus, different kinds of analysis regarding the EA exist, each relying on certain conditions and demands for models, methods, and techniques. In this paper we present a classification schema for EA analysis approaches to examine this topic. The classification schema is used to investigate the state-of-the-art of EA analysis by characterizing existing approaches according to the presented dimensions. Based on the results of this classification, future areas of research regarding EA analysis are derived. Key words: Enterprise architecture management, EA analysis, ex ante/ex post analysis, behavioral/structural analysis, EA analysis classification 1 Introduction and

management

Since (1996) Knight and Pretty published their study about the impact of catastrophes on shareholder value, the need for a business continuity management system (BCMS) became clear. Once a BCMS is in place, the corresponding risks can be insured against. The BS 25999 certificate can serve as proof of implementation. It requires defined business continuity plans (BCP). However, processes based on BCPs are rarely tested. Therefore, little knowledge is available to confirm their proper functioning and their non-functional properties. This paper addresses the verification of BCPs. We show how to model, simulate and verify normal business processes and business processes that are based on a BCP. As a formal method, we use process algebra and modal logic to explain the semantics of conceptual business process models. Our study places emphasis on questions regarding the potential capacity and duration of a process based on a BCP as well as those of an organizational security policy. By doing this, we are able to demonstrate that ex-ante evaluation is not only possible but also effective. 1

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Traditional Model Driven Development (MDD) frameworks have three critical issues: (1) abstraction gap between modeling and programming layers, (2) a lack of traceability between models and programs, and (3) a lack of customizability to support various combinations of modeling technologies and implementation/deployment technologies. In order to address these issues, this chapter proposes a new MDD framework, called Matilda, which is a framework to build execution runtime engines (or virtual machines) for software models. It directly executes models defined with certain modeling technologies such as UML and BPMN by automatically transforming them to executable code. Matilda is designed based on the Pipes and Filters architectural pattern, which allows for configuring its structure and behavior flexibly by replacing one plugin with another one or changing the order of plugins. Also, plugins can be deployed on multiple network hosts and seamlessly connect them to form a pipeline. This facilitates distributed software development in which developers collaboratively work at physically dispersed places. This chapter overviews Matilda’s architectural design, describes the implementations of Matilda-based virtual machines, and evaluates their performance.