Français Anglais
Accueil Annuaire Plan du site
Accueil > Production scientifique > Résultat majeur
Production scientifique
Résultat majeur : COVERAGE-BIASED RANDOM EXPLO-RATION OF LARGE MODELS AND APPLICATION TO TESTING
COVERAGE-BIASED RANDOM EXPLO-RATION OF LARGE MODELS AND APPLICATION TO TESTING
27 mars 2011

A. Denise, M.-C. Gaudel, S.-D. Gouraud, R. Lassaigne, J. Oudinet S. Peyronnet, STTT: Int. Jal on SOFTWARE TOOLS FOR TECHNOLOGY TRANSFER, DOI: 10.1007/s10009-011-0190-1
This paper presents several randomised algorithms for generating paths in large models according to a given coverage criterion. Using methods for counting combinatorial structures, these algorithms can efficiently explore very large models, based on a graphical representation by an automaton or by a product of several automata. This new approach can be applied to random exploration in order to optimise path coverage and can be generalised to take into account other coverage criteria, via the definition of a notion of randomised coverage satisfaction. Our main contributions are a method for drawing paths uniformly at random in composed models, i.e. models that are given as products of automata, first without and then with synchronisation; a new efficient approach to draw paths at random taking into account some other coverage criterion. Experimental results show promising agreement with theoretical predictions and significant improvement over previous randomised approaches. This work opens new perspectives for future studies of statistical testing and model checking, mainly to fight the combinatorial explosion problem.



Activités de recherche
  ° Test de Logiciels
  ° Algorithmique
  ° Combinatoire énumerative

Equipe
  ° Bioinformatique
  ° Parallélisme
  ° Test Formel et Exploration de Systèmes

Contact
  [aucun]
Résultats majeurs
BEST STUDENT PAPER AWARD (ML) AT ECML 2019
20 septembre 2019
Guillaume Doquet (A&O), Best Student Paper Award (category Machine Learning) at ECML 2019.

BEST PAPER AWARD - HPCS 2019 - ON SERVER-SIDE FILE ACCESS PATTERN MATCHING
17 juillet 2019
Francieli Zanon Boito¹ , Ramon Nou², Laércio Lima Pilla³, Jean Luca Bez⁴, Jean-François Méhaut¹, T

BEST FULL PAPER AWARD EDM 2019 - EDUCATIONAL DATA MINING
05 juillet 2019
DAS3H: Modeling Student Learning and Forgetting for Optimally Scheduling Distributed Practice of Ski

BEST PAPER AWARD - CODIT2019 - STOCHASTIC DUAL DYNAMIC INTEGER PROGRAMMING FOR A MULTI-ECHELON LOT-SIZING PROBLEM WITH REMANUFACTURING AND LOST SALES
14 mai 2019
Franco Quezada, Céline Gicquel and Safia Kedad-Sidhoum

BEST PAPER AWARD ICONS 2019: RESONANCE THINKING AND INDUCTIVE MACHINE LEARNING
06 mai 2019
Yves Kodratoff & Marta Franova