S\u00e9minaire transverse SAMOVAR<\/p>\n
Quand :<\/strong> lundi 29 mai 2017 \u00e0 14h00 Dr. Vincent Leroy (Universit\u00e9 de Grenoble)<\/p>\n Title:<\/strong> Debugging applications: a data mining approach<\/p>\n Abstract:<\/strong> Biographie:<\/strong> S\u00e9minaire transverse SAMOVAR Quand : lundi 29 mai 2017 \u00e0 14h00 O\u00f9 : salle G09, T\u00e9l\u00e9com SudParis, Evry. Dr. Vincent Leroy (Universit\u00e9 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. 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\nO\u00f9 :<\/strong> salle G09, T\u00e9l\u00e9com SudParis, Evry.<\/p>\n
\nDebugging applications can be a tedious task. Traditional test methods focus
\non identifying functional bugs in which a function outputs an erroneous value.
\nHowever, more subtle bugs can occur in concurrent systems, such as a function
\ncall in a video decoding application occasionally missing its deadline and
\ncausing a visual artifact. In this seminar, I will show how data mining can
\nhelp developers better understand these issues.
\nIn the first part of this presentation, I will consider the case of embedded
\nsystems and multimedia applications. The developer first records a trace of
\nthe application, containing both normal activity and misbehaviors. Our
\nframework, using a combination of clustering and pattern mining, identifies
\nerroneous activities and finds which system behavior they are correlated to.
\nThe second part of the presentation will focus on model checking. In this
\ncase, the developer can ask a solver to verify a property (such as B is never
\nexecuted after A), and the solver usually returns a counter-example trace
\ncontaining hundreds of events. Our approach, based on execution graph
\nanalysis, generalizes and abstracts counter-examples to help developers focus
\non the key parts of their program that really impact the bug.<\/p>\n
\nVincent Leroy is an associate professor at the University of Grenoble. He is a
\npermanent member of the Scalable Information Discovery and Exploitation
\n(SLIDE) research group. He earned a Masters degree in computer science from
\nINSA Rennes, France in 2007 and a PhD degree on large-scale distributed
\nsystems for social applications from Inria Rennes, France, in 2010. From 2010
\nto 2012, he worked on distributed search engines at Yahoo! Research Labs in
\nBarcelona, Spain. Vincent’s research interests lie at the intersection of
\ndistributed system and large-scale data management; he builds scalable
\nalgorithms and systems to analyze data produced by a variety of real-world
\napplications.<\/p>\n","protected":false},"excerpt":{"rendered":"