scholarly journals Supporting efficient and advanced omniscient debugging for xDSMLs

Author(s):  
Erwan Bousse ◽  
Jonathan Corley ◽  
Benoit Combemale ◽  
Jeff Gray ◽  
Benoit Baudry
Keyword(s):  
2021 ◽  
Vol 206 ◽  
pp. 102630
Author(s):  
Kazumasa Shimari ◽  
Takashi Ishio ◽  
Tetsuya Kanda ◽  
Naoto Ishida ◽  
Katsuro Inoue

2018 ◽  
Vol 137 ◽  
pp. 261-288 ◽  
Author(s):  
Erwan Bousse ◽  
Dorian Leroy ◽  
Benoit Combemale ◽  
Manuel Wimmer ◽  
Benoit Baudry
Keyword(s):  

2007 ◽  
Vol 42 (10) ◽  
pp. 535-552 ◽  
Author(s):  
Guillaume Pothier ◽  
Éric Tanter ◽  
José Piquer
Keyword(s):  

Author(s):  
Vincent J. Koeman ◽  
Koen V. Hindriks ◽  
Catholijn M. Jonker

The main goal of our demonstration is to show how omniscient debugging can be applied in practice to cognitive agents. A concrete implementation of the mechanisms proposed in Koeman et. al [2017] has been created for the GOAL agent programming language in the Eclipse environment, integrated with the source-level debugger of Koeman et. al [2016], thus fully implementing the proposal within a state-of-the-art setting. The implementation will be used together with typical agent programs to demonstrate its practical use.


Author(s):  
Vincent J. Koeman ◽  
Koen V. Hindriks ◽  
Catholijn M. Jonker

For real-time programs reproducing a bug by rerunning the system is likely to fail, making fault localization a time-consuming process. Omniscient debugging is a technique that stores each run in such a way that it supports going backwards in time. However, the overhead of existing omniscient debugging implementations for languages like Java is so large that it cannot be effectively used in practice. In this paper, we show that for agent-oriented programming practical omniscient debugging is possible. We design a tracing mechanism for efficiently storing and exploring agent program runs. We are the first to demonstrate that this mechanism does not affect program runs by empirically establishing that the same tests succeed or fail. Usability is supported by a trace visualization method aimed at more effectively locating faults in agent programs.


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