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Observation strategies for event detection with incidence on runtime verification: theory, algorithms, experimentation

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Abstract

Many applications (such as system and user monitoring, runtime verification, diagnosis, observation-based decision making, intention recognition) all require to detect the occurrence of an event in a system, which entails the ability to observe the system. Observation can be costly, so it makes sense to try and reduce the number of observations, without losing full certainty about the event’s actual occurrence. In this paper, we propose a formalization of this problem. We formally show that, whenever the event to be detected follows a discrete spatial or temporal pattern, then it is possible to reduce the number of observations. We discuss exact and approximate algorithms to solve the problem, and provide an experimental evaluation of them. We apply the resulting algorithms to verification of linear temporal logics formulæ. Finally, we discuss possible generalizations and extensions, and, in particular, how event detection can benefit from logic programming techniques.

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Authors and Affiliations

  1. Centro de Inteligência Artificial (CENTRIA), Departamento de Informática, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Caparica, Portugal

    Marco Alberti & Luís Moniz Pereira

  2. Dept. of Science and Technology, ITN, Linköping University, Norrköping, Sweden

    Pierangelo Dell’Acqua

Authors
  1. Marco Alberti
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  2. Pierangelo Dell’Acqua
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  3. Luís Moniz Pereira
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Correspondence to Marco Alberti.

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Alberti, M., Dell’Acqua, P. & Pereira, L.M. Observation strategies for event detection with incidence on runtime verification: theory, algorithms, experimentation. Ann Math Artif Intell 62, 161–186 (2011). https://doi.org/10.1007/s10472-011-9259-5

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