Detecting Imperfect Patterns in Event Streams Using Local Search

  • Adele E. Howe
Part of the Lecture Notes in Statistics book series (LNS, volume 112)


Recurring patterns in event streams may indicate causal influences. Such patterns have been used as the basis of software debugging. One technique, dependency detection, for finding these patterns requires exhaustive search and perfect patterns, two characteristics that are unrealistic for event streams extracted from software executions. This paper presents an enhanced version of dependency detection that uses a more flexible pattern matching scheme to extend the types of patterns detected and local search to reduce the computational demands. The new version was tested on real and artificial data to determine whether local search is effective for detecting strong patterns.


Local Search Contingency Table Synthetic Data Significant Dependency Target Event 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag New York, Inc. 1996

Authors and Affiliations

  • Adele E. Howe

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