Abstract
Analyzing potential data inaccuracy is an important aspect of business process design that has been mostly overlooked so far. To this end, process models should express the relevant information to support such analysis. In this paper we propose a formal framework for design-time analysis of potential data inaccuracy situations. In particular, we define a property of Data Inaccuracy Awareness which indicates the ability to know at runtime whether data values are accurate representations of real values. We propose an algorithm for analyzing this property at design time based on a process model. A preliminary evaluation of the applicability and scalability of the algorithm using a benchmark collection of process models is reported.
The first and second authors were supported by the Israel Science Foundation under grant agreement no. 856/13.
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- 1.
Premise 1 restricts our approach to state variables whose volatility is not high. For example, a state variable depicting the location of a moving car does not subscribe to this premise, while a state variable depicting the address of a customer does. This premise entails that the designer has to identify for which data items this analysis approach would be appropriate.
- 2.
Our purpose is to reason about potential data inaccuracy situations at design-time while acknowledging runtime situations. Thus, exploring concurrency cases where data operations can execute simultaneously or at any order is vital. For that reason, a clear assignment of data operations to blocks in the net is essential.
- 3.
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Evron, Y., Soffer, P., Zamansky, A. (2018). Design-Time Analysis of Data Inaccuracy Awareness at Runtime. In: Teniente, E., Weidlich, M. (eds) Business Process Management Workshops. BPM 2017. Lecture Notes in Business Information Processing, vol 308. Springer, Cham. https://doi.org/10.1007/978-3-319-74030-0_47
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