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On the use of computational geometry to detect software faults at runtime
Conference proceeding

On the use of computational geometry to detect software faults at runtime

Edward Stehle, Kevin Lynch, Maxim Shevertalov, Chris Rorres and Spiros Mancoridis
Proceedings of the 7th international conference on autonomic computing, pp 109-118
07 Jun 2010
DOI: https://doi.org/10.1145/1809049.1809069

Abstract

autonomic computational geometry fault tolerance
Despite advances in software engineering, software faults continue to cause system downtime. Software faults are difficult to detect before the system fails, especially since the first symptom of a fault is often system failure itself. This paper presents a computational geometry technique and a supporting tool to tackle the problem of timely fault detection during the execution of a software application. The approach in- volves collecting a variety of runtime measurements and building a geometric enclosure, such as a convex hull, which represents the normal (i.e., non-failing) operating space of the application being monitored. When collected runtime measurements are classified as being outside of the enclosure, the application is considered to be in an anomalous (i.e., failing) state. This paper presents exper- imental results that illustrate the advantages of using a computational geometry approach over the distance based approaches of Chi-Squared and Mahalanobis distance. Additionally, we present results illustrating the advantages of using the convex-hull enclosure for fault detection in favor of a simpler enclosure such as a hyperrectangle

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