Reachability in Database-driven Systems with Numerical Attributes under Recency Bounding

Abdulla, Parosh Aziz; Aiswarya, C.; Atig, Mohamed Faouzi; Montali, Marco

doi:10.1145/3294052.3319705

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…This is the case of integrated models for business processes and data, extensively studied in the last two decades within business process management and database theory (Reichert 2012;Calvanese, De Giacomo, and Montali 2013). AI techniques have been extremely successful to handle a variety of reasoning tasks over such integrated models, ranging from static analysis (Bagheri Hariri et al 2013;De Masellis et al 2017;Abdulla et al 2019) to online monitoring (De Masellis, Maggi, and Montali 2014;Maggi et al 2011).…”

Section: Introductionmentioning

confidence: 99%

Strategy Synthesis for Data-Aware Dynamic Systems with Multiple Actors

Leoni

Felli

Montali

2020

Proceedings of the Seventeenth International Conference on Principles of Knowledge Representation and Reasoning

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The integrated modeling and analysis of dynamic systems and the data they manipulate has been long advocated, on the one hand, to understand how data and corresponding decisions affect the system execution, and on the other hand to capture how actions occurring in the systems operate over data. KR techniques proved successful in handling a variety of tasks over such integrated models, ranging from verification to online monitoring. In this paper, we consider a simple, yet relevant model for data-aware dynamic systems (DDSs), consisting of a finite-state control structure defining the executability of actions that manipulate a finite set of variables with an infinite domain. On top of this model, we consider a data-aware version of reactive synthesis, where execution strategies are built by guaranteeing the satisfaction of a desired linear temporal property that simultaneously accounts for the system dynamics and data evolution.

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