MAFALDA: Microkernel Assessment by Fault Injection and Design Aid
EDCC-3 Proceedings of the Third European Dependable Computing Conference on Dependable Computing
GOOFI: Generic Object-Oriented Fault Injection Tool
DSN '01 Proceedings of the 2001 International Conference on Dependable Systems and Networks (formerly: FTCS)
PRDC '02 Proceedings of the 2002 Pacific Rim International Symposium on Dependable Computing
Comparing Operating Systems Using Robustness Benchmarks
SRDS '97 Proceedings of the 16th Symposium on Reliable Distributed Systems
A Framework for Assessing Dependability in Distributed Systems with Lightweight Fault Injectors
IPDS '00 Proceedings of the 4th International Computer Performance and Dependability Symposium
PRDC '04 Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC'04)
Benchmarking Operating System Dependability: Windows 2000 as a Case Study
PRDC '04 Proceedings of the 10th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC'04)
A dependability benchmark for OLTP application environments
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Investigation of failure causes in workload-driven reliability testing
Fourth international workshop on Software quality assurance: in conjunction with the 6th ESEC/FSE joint meeting
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Our paper presents a novel approach for identifying the key infrastructural factors determining the behavior of systems in the presence of faults by the application of intelligent data processing methods on data sets obtained from dependability benchmarking experiments. Our approach does not rely on a-priori assumptions or human intuition about the dominant aspects enabling this way the investigation of highly complex COTS-based systems. The proposed approach is demonstrated using a commercial data mining tool from IBM on the data obtained from experiments conducted using the DBench-OLTP dependability benchmark. Results obtained with the proposed technique identified important key factors impacting performance and dependability that could not have been revealed by the dependability benchmark measures.