We present our efforts on the formalization and automated formal verification of data-intensive applications based on the Storm technology, a well known and pioneering framework for developing streaming applications. The approach is based on the so-called array-based systems formalism, introduced by Ghilardi et al., a suitable abstraction of infinite-state systems that we used to model the runtime behavior of Storm-based applications. The formalization consists of quantified first-order formulae symbolically representing array-based systems. The verification consists in checking whether some safety property holds or not for the system. Both formalization and verification are performed in the same framework, namely the state-of-the-art Cubicle model checker.

Formal verification of data-intensive applications through model checking modulo theories

Bersani, Marcello M.;Marconi, Francesco;Rossi, Matteo;
2017-01-01

Abstract

We present our efforts on the formalization and automated formal verification of data-intensive applications based on the Storm technology, a well known and pioneering framework for developing streaming applications. The approach is based on the so-called array-based systems formalism, introduced by Ghilardi et al., a suitable abstraction of infinite-state systems that we used to model the runtime behavior of Storm-based applications. The formalization consists of quantified first-order formulae symbolically representing array-based systems. The verification consists in checking whether some safety property holds or not for the system. Both formalization and verification are performed in the same framework, namely the state-of-the-art Cubicle model checker.
2017
SPIN 2017 - Proceedings of the 24th ACM SIGSOFT International SPIN Symposium on Model Checking of Software
9781450350778
Array-based systems; Data-intensive applications; Formal verification; Infinite-state model checking; Storm technology; Artificial Intelligence; Software; Computer Science Applications1707 Computer Vision and Pattern Recognition
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1045522
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