Séminaire transverse SAMOVAR

Quand : lundi 29 mai 2017 à 14h00
Où : salle G09, Télécom SudParis, Evry.

Dr. Vincent Leroy (Université de Grenoble)

Title: Debugging applications: a data mining approach

Abstract:
Debugging applications can be a tedious task. Traditional test methods focus
on identifying functional bugs in which a function outputs an erroneous value.
However, more subtle bugs can occur in concurrent systems, such as a function
call in a video decoding application occasionally missing its deadline and
causing a visual artifact. In this seminar, I will show how data mining can
help developers better understand these issues.
In the first part of this presentation, I will consider the case of embedded
systems and multimedia applications. The developer first records a trace of
the application, containing both normal activity and misbehaviors. Our
framework, using a combination of clustering and pattern mining, identifies
erroneous activities and finds which system behavior they are correlated to.
The second part of the presentation will focus on model checking. In this
case, the developer can ask a solver to verify a property (such as B is never
executed after A), and the solver usually returns a counter-example trace
containing hundreds of events. Our approach, based on execution graph
analysis, generalizes and abstracts counter-examples to help developers focus
on the key parts of their program that really impact the bug.

Biographie:
Vincent Leroy is an associate professor at the University of Grenoble. He is a
permanent member of the Scalable Information Discovery and Exploitation
(SLIDE) research group. He earned a Masters degree in computer science from
INSA Rennes, France in 2007 and a PhD degree on large-scale distributed
systems for social applications from Inria Rennes, France, in 2010. From 2010
to 2012, he worked on distributed search engines at Yahoo! Research Labs in
Barcelona, Spain. Vincent’s research interests lie at the intersection of
distributed system and large-scale data management; he builds scalable
algorithms and systems to analyze data produced by a variety of real-world
applications.