Tue 27 Oct 2015 14:00 - 14:30 at Grand Station 2 - Model Execution and Verification Chair(s): Davide Di Ruscio

Omniscient debugging is a promising technique that relies on execution traces to enable free traversal of the states reached by a system during an execution. While some General-Purpose Languages (GPLs) already have support for omniscient debugging, developing such a complex tool for any executable Domain-Specific Modeling Language (xDSML) remains a challenging and error prone task. A solution to this problem is to define a generic omniscient debugger for all xDSMLs. However, generically supporting any xDSML both compromises the efficiency and the usability of such an approach. Our contribution relies on a partly generic omniscient debugger supported by generated domain-specific trace management facilities. Being domain-specific, these facilities are tuned to the considered xDSML for better efficiency. Usability is strengthened by providing multidimensional omniscient debugging. Results show that our approach is on average 3.0 times more efficient in memory and 5.03 more efficient in time when compared to a generic solution that copies the model at each step.

Tue 27 Oct

Displayed time zone: Eastern Time (US & Canada) change

13:30 - 15:00
Model Execution and VerificationSLE at Grand Station 2
Chair(s): Davide Di Ruscio University of L'Aquila
13:30
30m
Talk
Weaving Concurrency in eXecutable Domain-Specific Modeling Languages
SLE
Florent Latombe University of Toulouse, France, Xavier Crégut University of Toulouse, France, Benoit Combemale INRIA, France, Julien DeAntoni , Marc Pantel University of Toulouse, France
DOI Pre-print Media Attached File Attached
14:00
30m
Talk
Supporting Efficient and Advanced Omniscient Debugging for xDSMLs
SLE
Erwan Bousse IRISA, France, Jonathan Corley University of Alabama, USA, Benoit Combemale INRIA, France, Jeff Gray University of Alabama, USA, Benoit Baudry INRIA, France
Link to publication DOI File Attached
14:30
30m
Talk
Using Decision Rules for Solving Conflicts in Extended Feature Models
SLE
Lina Ochoa University of Los Andes, Colombia, Oscar González-Rojas University of Los Andes, Colombia, Thomas Thüm TU Braunschweig, Germany
DOI