A Framework for Automatic Debugging of Functional and Degradation Failures

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Cardoso, N (Author) Other; Rui Abreu (Author) FEUP; Feldman, A (Author) Other; de Kleer, J (Author) Other

Conference proceedings International

Title: ECAI 2016: 22ND EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE

Pages: 569-576

22nd European Conference on Artificial Intelligence (ECAI)

Hague, NETHERLANDS, AUG 29-SEP 02, 2016

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 2 Citations

Other information

Authenticus ID: P-00K-SS1

DOI: 10.3233/978-1-61499-672-9-569

Abstract (EN): Software diagnosis is a particularly challenging problem for modern systems, which may consist of dozens, if not hundreds, of components computing on concurrent and potentially distributed platforms, and using infrastructure and services built by many organizations. We propose a framework that generalizes state-of-the-art classical reasoning-based fault diagnosis which tolerates observation uncertainty and addresses degradation of quality of service. Empirical evaluation involving 27 000 highly realistic synthetic scenarios demonstrates an average accuracy improvement of 20% (with 99% statistical significance) which is considerable in the domain of Software Fault Localization (SFL). We measure the improvement in accuracy on well-established SFL performance metrics.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 8