Supporting Efficient and Advanced Omniscient Debugging for xDSMLs
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.
Slides (2015-10-SLE-OmniscientDebugging.pdf) | 4.87MiB |
Tue 27 OctDisplayed 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 30mTalk | 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 30mTalk | 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 30mTalk | 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 University of Ulm DOI |