Reference : A Temporal Model for Interactive Diagnosis of Adaptive Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/36721
A Temporal Model for Interactive Diagnosis of Adaptive Systems
English
Mouline, Ludovic mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Benelallam, Amine mailto [Univ Rennes > Inria, CNRS, IRISA > DiverSE]
Fouquet, François mailto [DataThings S.A.R.L.]
Bourcier, Johann mailto [Univ Rennes > Inria, CNRS, IRISA > DiverSE]
Barais, Olivier mailto [Univ Rennes > Inria, CNRS, IRISA > DiverSE]
Sep-2018
2018 IEEE International Conference on Autonomic Computing (ICAC)
Mouline, Ludovic mailto
Benelallam, Amine mailto
Fouquet, François mailto
Bourcier, Johann mailto
Barais, Olivier mailto
Yes
No
International
IEEE International Conference on Autonomic Computing (ICAC)
from 03-09-2018 to 07-09-2018
Trento
Italy
[en] Adaptive systems ; Traceability ; Diagnosis ; model-driven engineering
[en] The evolving complexity of adaptive systems impairs our ability to deliver anomaly-free solutions. Fixing these systems require a deep understanding on the reasons behind decisions which led to faulty or suboptimal system states. Developers thus need diagnosis support that trace system states to the previous circumstances –targeted requirements, input context– that had resulted in these decisions. However, the lack of efficient temporal representation limits the tracing ability of current approaches. To tackle this problem, we first propose a knowledge formalism to define the concept of a decision. Second, we describe a novel temporal data model to represent, store and query decisions as well as their relationship with the knowledge (context, requirements, and actions). We validate our approach through a use case based on the smart grid at Luxembourg. We also demonstrate its scalability both in terms of execution time and consumed memory.
http://hdl.handle.net/10993/36721

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