Spectrum-based fault diagnosis for service-oriented software systems

Chen, Cuiting; Groß, Hans-Gerhard; Zaidman, Andy

doi:10.1109/soca.2012.6449440

Cited by 5 publications

(10 citation statements)

References 24 publications

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“…Although SFL can effectively be used in diagnosing faulty services, experiments performed for our previous work [7] show that incorrect diagnoses are more likely, if services are tightly coupled. In other words, if a service S 1 always invokes another service S 2 , the diagnosis is such that both services S 1 and S 2 will be convicted, leading to incorrect or inconclusive diagnoses.…”

Section: Introductionmentioning

confidence: 91%

“…This allows the implementation of online monitoring to record the block-hit spectra for SFL with minimum amendments, yielding a slender design. Our prototypical implementation is summarized briefly in the following (more details in [7]).…”

Section: Implementation Of Sfl For Service-based Systemsmentioning

confidence: 99%

“…Recent work [7] demonstrates that spectrum-based fault localization (SFL), a statistics-based diagnosis technique can effectively be used in order to pinpoint faulty components in service-based systems. SFL works by automatically inferring a diagnosis from observed symptoms [8].…”

Section: Introductionmentioning

confidence: 99%

“…the ser-vices in a service-based system, and the symptoms are observations about service involvement in system activation, i.e. the service transactions, plus pass/fail information for each transaction [7], [9]. SFL is based on the assumption that a service is more likely to be faulty, if it participates more in failing transactions, and it mimics how a human diagnostician would exonerate parts of a system that cannot be used to explain a particular failure observation.…”

Section: Introductionmentioning

confidence: 99%

“…Careful analysis of the experiments performed for [7] reveals that the difficulty of tight coupling for the SFL approach can be explained either by the architecture of the system and how services interact, or by the granularity of the observations used for SFL. Whereas, in the first instance, it would be rather difficult to try and rearrange the architecture in order to decouple services for any individual system configuration; in the second instance, it would be relatively easy to introduce more observation points in the architecture, and thus increase the level of granularity, in order to support the calculation of a conclusive diagnosis.…”

Section: Introductionmentioning

confidence: 99%

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Improving Service Diagnosis through Increased Monitoring Granularity

Chen

Groß

Zaidman

2013

2013 IEEE 7th International Conference on Software Security and Reliability

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Due to their loose coupling and highly dynamic nature, service-oriented systems offer many benefits for realizing fault tolerance and supporting trustworthy computing. They enable automatic system reconfiguration in case that a faulty service is detected. Spectrum-based fault localization (SFL) is a statistics-based diagnosis technique that can effectively be applied to pinpoint problematic services. It works by monitoring service usage in system transactions and comparing service coverage with pass/fail observations. SFL exhibits poor performance in diagnosing faulty services in cases when services are tightly coupled. In this paper, we study how and to which extent an increase in monitoring granularity can help to improve correct diagnosis of tightly coupled faulty services. We apply SFL in a real service-based system, for which we show that 100% correct identification of faulty services can be achieved through an increase in the monitoring granularity.

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Section: Introductionmentioning

confidence: 91%

Section: Implementation Of Sfl For Service-based Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Improving Service Diagnosis through Increased Monitoring Granularity

Chen

Groß

Zaidman

2013

2013 IEEE 7th International Conference on Software Security and Reliability

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Analysis of service diagnosis improvement through increased monitoring granularity

2015

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Due to their loosely coupled and highly dynamic nature, service-oriented systems offer many benefits for realizing fault tolerance and supporting trustworthy computing. They enable automatic system reconfiguration when a faulty service is detected. Spectrum-based fault localization (SFL) is a statistics-based diagnosis technique that can be effectively applied to pinpoint problematic services. However, SFL exhibits poor performance in diagnosing services which are tightly interacted. Previous research suggests that an increase in the number of monitoring locations may improve the diagnosability for tight interaction. In this paper, we analyze the trade-offs between the diagnosis improvement through increased monitoring granularity and the overhead caused by the introduction of more monitors, when diagnosing tightly interacted faulty services. We apply SFL in a service-based system, for which we show that 100 % correct identification of faulty services can be achieved through the increased monitoring granularity. We assess the overhead with increased monitoring granularity and compare this with the original monitoring setup. Our experimental results show that the monitoring at the service communication level causes relatively high overhead, whereas the monitoring overhead at a finer level of granularity, i.e., at the service implementation level, is much lower, but highly dependent on the number of monitors deployed.& Cuiting Chen

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