Software Behaviour Correlation in a Redundant and Diverse Environment Using the Concept of Trace Abstraction

ahamou-lhadj — Wed, 13 Nov 2013 22:49:14 +0000

A. Hamou-Lhadj, S. S. Murtaza, W. Fadel, A. Mehrabian, M. Couture, R. Khoury, "Software Behaviour Correlation in a Redundant and Diverse Environment Using the Concept of Trace Abstraction," In Proc. of the ACM 2013 Research in Adaptive and Convergent Systems Conference (RACS'13), Montrela, QC, Canada 2013.

Redundancy and diversity has been shown to be an effective approach for ensuring service continuity (an important requirement for autonomic systems) despite the presence of anomalies due to attacks or faults. In this paper, we focus on operating system (OS) diversity, which is useful in helping a system survive kernel-level anomalies. We propose an approach for detecting anomalies in the presence of OS diversity. We achieve this by comparing kernel-level traces generated from instances of the same application deployed on different OS. Our trace correlation process relies on the concept of trace abstraction, in which low-level system events are transformed into higher-level concepts, freeing the trace from OS-related events. We show the effectiveness of our approach through a case study, in which we selected Linux and FreeBSD as target OS. We also report on lessons learned, setting the ground for future research.

Mining Telecom System Logs to Facilitate Debugging Tasks,

ahamou-lhadj — Wed, 13 Nov 2013 22:46:52 +0000

A. Larsson, A. Hamou-Lhadj, “Mining Telecom System Logs to Facilitate Debugging Tasks,” In Proc. of the 29th International Conference on Software Maintenance (ICSM’13), Eindhoven, The Netherlands, 2013.

Telecommunication systems are monitored continuously to ensure quality and continuity of service. When an error or an abnormal behaviour occurs, software engineers resort to the analysis of the generated logs for troubleshooting. The problem is that, even for a small system, the log data generated after running the system for a period of time can be considerably large. There is a need to automatically mine important information from this data. There exist studies that aim to do just that, but their focus has been mainly on software applications, paying little attention to network information used by telecom systems. In this paper, we show how data mining techniques, more particularly the ones based on mining frequent itemsets, can be used to extract patterns that characterize the main behaviour of the traced scenarios. We show the effectiveness of our approach through a representative study conducted in an industrial setting.

Automated monitoring and debugging of large scale manycore heterogeneous systems - Trace analysis

Software Behaviour Correlation in a Redundant and Diverse Environment Using the Concept of Trace Abstraction

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Mining Telecom System Logs to Facilitate Debugging Tasks,

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