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Nowadays, organizations have to adjust their business processes along with the changing environment in order to maintain a competitive advantage. Changing a part of the system to support the business process implies changing the entire system, which leads to complex redesign activities. In this paper, a bottom-up process mining and simulation-based methodology is proposed to be employed in redesign activities. The methodology starts with identifying relevant performance issues, which are used as basis for redesign. A process model is "mined" and simulated as a representation of the existing situation, followed by the simulation of the redesigned process model as prediction of the future scenario. Finally, the performance criteria of the current business process model and the redesigned business process model are compared such that the potential performance gains of the redesign can be predicted. We illustrate the methodology with three case studies from three different domains: gas industry, government institution and agriculture.

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Business processes design and execution environments increasingly need support from modular services in service compositions to offer the flexibility required by rapidly changing requirements. With each evolution, however, the service composition must continue to adhere to laws and regulations, resulting in a demand for automated compliance checking. Existing approaches, if at all, either offer only verification after the fact or linearize models to such an extent that parallel information is lost. We propose a mapping of service compositions to Kripke structures by using colored Petri nets. The resulting model allows preventative compliance verification using wellknown temporal logics and model checking techniques while providing full insight into parallel executing branches and the local next invocation. Furthermore, the mapping causes limited state explosion, and allows for significant further model reduction. The approach is validated on a case study from a telecom company in Australia and evaluated with respect to performance and expressiveness. We demonstrate that the proposed mapping has increased expressiveness while being less vulnerable to state explosion than existing approaches, and show that even large service compositions can be verified preventatively with existing model checking techniques.

Organisations typically have to cope with large numbers of business rules and existing regulations governing the business in which they operate. Due to the size and complexity of those rules, maintenance is difficult and it is increasingly complicated to ensure that each business process adheres to those rules. As such, automated extraction of business processes from rules has a number of clear advantages: (1) visualisation of all possible executions allowed by the rules, (2) automated execution and compliance by design, (3) identification of "inefficiencies" in the business rules. Existing approaches, however, only allow to generate partial traces based on input specifications and cannot handle many different input cases resulting in a full process. This paper presents a formal method to visualise and operationalise such sets of rules as a verifiable business process that is compliant by design and allows us to analyse all possible execution paths. In addition, it maintains information of all distinct input cases, to preserve dependencies between consecutive exclusive paths.

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In order to improve the flexibility of information systems, an increasing amount of business processes is being automated by implementing tasks as modular services in service compositions. As organizations are required to adhere to laws and regulations, with this increased flexibility there is a demand for automated compliance checking of business processes. Model checking is a technique which exhaustively and automatically verifies system models against specifications of interest, e.g. a finite state machine against a set of logic formulas. When model checking business processes, existing approaches either cause large amounts of overhead, linearize models to such an extent that activity parallelization is lost, offer only checking of runtime execution traces, or introduce new and unknown logics. In order to fully benefit from existing model checking techniques, we propose a mapping from workflow patterns to a class of labeled transition systems known as Kripke structures. With this mapping, we provide pre-runtime compliance checking using well-known branching time temporal logics. The approach is validated on a complex abstract process which includes a deferred choice, parallel branching, and a loop. The process is modeled using the Business Process Model and Notation (BPMN) standard, converted into a colored Petri net using the workflow patterns, and subsequently translated into a Kripke structure, which is then used for verification.