@INPROCEEDINGS{MarwedeRohrHoornHasselbring2009AutomaticFailureDiagnosisInDistributedLargeScaleSoftwareSystemsBasedOnTimingBehaviorAnomalyCorrelation,
  author = {Nina S. Marwede and Matthias Rohr and Andr\'{e} van Hoorn
	and Wilhelm Hasselbring},
  title = {Automatic Failure Diagnosis in Distributed Large-Scale
	Software Systems based on Timing Behavior Anomaly Correlation},
  slides = {http://pc-rohr.informatik.uni-oldenburg.de/pubPapers/MarwedeRohrHoornHasselbring2008AutomaticFailureDiagnosisSupportInDistributedLargeScaleSoftwareSystemsBasedOnTimingBehaviorAnomalyCorrelation-slides.pdf},
  booktitle = {Proceedings of the 13th European Conference on Software
	Maintenance and Reengineering (CSMR'09)},
  year = {2009},
  publisher = {IEEE},
  editor = {Andreas Winter and Rudolf Ferenc and Jens Knodel},
  isbn = {978-0-7695-3589-0},
  location = {Kaiserslautern, Germany},
  month = mar,
  pages ={47--57},
  doi = {10.1109/CSMR.2009.15},
  keywords = {failure diagnosis, fault localization, software faults, software
	dependability, anomaly detection, component dependency graphs},
  abstract = {Manual failure diagnosis in large-scale software systems is
	time-consuming and error-prone. Automatic failure diagnosis support
	mechanisms can potentially narrow down, or even localize faults within a
	very short time which both helps to preserve system availability. A
	large class of automatic failure diagnosis approaches consists of two
	steps: 1) computation of component anomaly scores; 2) global correlation
	of the anomaly scores for fault localization.

	In this paper, we present an architecture-centric approach for the
	second step. In our approach, component anomaly scores are correlated
	based on architectural dependency graphs of the software system and a
	rule set to address error propagation. Moreover, the results are
	graphically visualized in order to support fault localization and to
	enhance maintainability. The visualization combines architectural
	diagrams automatically derived from monitoring data with failure
	diagnosis results. In a case study, the approach is applied to a
	distributed sample Web application which is subject to fault injection.}
}

@MASTERSTHESIS{Marwede2008AutomaticFailureDiagnosisBasedOnTimingBehaviorAnomalyCorrelationInDistributedJavaWebApplications,
  author = {Nina Sophie Marwede},
  title = {Automatic Failure Diagnosis based on Timing Behavior Anomaly
	Correlation in Distributed Java Web Applications},
  school = {Carl von Ossietzky Universit{\"a}t Oldenburg, Germany},
  year = {2008},
  month = aug,
  abstract = {One approach to handling software failures, especially in
	large distributed systems, is the monitoring of components for quick
	reaction and recovery to reduce downtimes and maintenance costs. In
	previous work, our group has developed tools to monitor and evaluate the
	timing behavior of Java software systems to detect anomalies, which may
	be indicators of erroneous behavior.
	
	This diploma thesis enhances the approach to isolate the root cause for
	failures in distributed systems. Existing technologies are connected and
	extended to aggregate anomalies to a failure diagnosis. An anomaly
	correlator is developed that combines timing behavior anomalies using
	derived dependency graphs. It is then applied to a sample application
	under the influence of workload generation and fault injection. The
	results are visualized as colored graphs that can be exported to
	various image formats.},
  comment = {Diplomarbeit, Department of Computing Science, University of
	Oldenburg, Germany},
  url = {http://ninamarwede.de/pub/Marwede2008AutomaticFailureDiagnosisBasedOnTimingBehaviorAnomalyCorrelationInDistributedJavaWebApplications.pdf}
}

@UNPUBLISHED{Marwede2007EntwicklungVonAmeisenstrassenMitVirtuellenPheromonen,
  author = {Nina Sophie Marwede},
  title = {Entwicklung von Ameisenstra{\ss}en mit virtuellen Pheromonen},
  school = {Carl von Ossietzky Universit{\"a}t Oldenburg, Germany},
  note = {Not formally published},
  year = {2007},
  month = sep,
  abstract = {Ameisen kommunizieren unter anderem durch das Verteilen von
	Pheromonen in ihrer Umgebung zur Markierung von Wegen und Futterquellen.
	Ziel dieser Arbeit ist nicht die biologisch korrekte Simulation des
	Verhaltens der Ameisen, sondern eine anschauliche Reproduktion und
	Experimente mit der Auswirkung dieses Verhaltens: die Entstehung von
	Ameisenstra{\ss}en. Au{\ss}erdem werden M{\"o}glichkeiten der
	technischen Nutzbarkeit dieser Strukturbildung betrachtet und eine
	Heuristik f{\"u}r das Problem des Handlungsreisenden implementiert.},
  url = {http://ninamarwede.de/pub/Marwede2008AutomaticFailureDiagnosisBasedOnTimingBehaviorAnomalyCorrelationInDistributedJavaWebApplications.pdf}
}