STIC-AmSud projet with Argentina and Chile
Application of a Digiteo chair
Abstract
Diagnosability and predictability are important system properties, checked at design stage, that determine with certainty the past or future occurrence of a given fault in a partially observable system, based on its model and a sequence of observations. They are part of safety analysis and building of robust systems and allow the automatic generation of on-line diagnosers to be embedded into the system. This thesis will focus on designing and implementing efficient diagnosability and predictability checking and diagnoser synthesis methods for distributed discrete-event systems (as automata or Petri nets), emphasizing incremental building and compositionality properties. Both accurate and probabilistic frameworks will be studied. Features as defining optimal observability for ensuring diagnosability or predictability and dealing with dynamic architecture of systems will be considered, as well as possible extension to hybrid (continuous/discrete) systems.
Context
The work will rely on several important results about probabilistic diagnosability and distributed diagnosability (and very recently distributed predictability) obtained by PhD and postdocs these past years under the supervision of P. Dague.
Objectives
Developing formal methods and derived tools for efficient checking of diagnosability and predictability properties for large distributed systems, based on a modular and compositional approach, in order to design safer systems.
Work program
Extra information
Prerequisite
Master (M2R) in Computer Science.
Familiarity with formal methods and discrete-event systems.
Détails
Expected funding
Institutional funding
Status of funding
Expected
Candidates
Utilisateur
philippe.dague
Créé
Mardi 12 mars 2013 17:52:03 CET
dernière modif.
Mardi 12 mars 2013 17:52:03 CET
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Connexion
Ecole Doctorale Informatique Paris-Sud
Directrice
Nicole Bidoit Assistante
Stéphanie Druetta Conseiller aux thèses
Dominique Gouyou-Beauchamps
ED 427 - Université Paris-Sud
UFR Sciences Orsay
Bat 650 - aile nord - 417
Tel : 01 69 15 63 19
Fax : 01 69 15 63 87
courriel: ed-info à lri.fr