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Autonomic Computing, International Conference on (2005)
Seattle, Washington
June 13, 2005 to June 16, 2005
ISBN: 0-7965-2276-9
pp: 101-110
Mark Brodie , IBM T.J. Watson Research Center
Sheng Ma , IBM T.J. Watson Research Center
Guy Lohman , IBM Almaden Research Center
Laurent Mignet , IBM India Research Lab
Natwar Modani , IBM India Research Lab
Mark Wilding , IBM Toronto Development Lab
Jon Champlin , Lotus Development Lab
Peter Sohn , Lotus Development Lab
ABSTRACT
We present an architecture for and prototype of a system for quickly detecting software problem recurrences. Re-discovery of the same problem is very common in many large software products and is a major cost component of product support. At run-time, when a problem occurs, the system collects the problem symptoms, including the program call-stack, and compares it against a database of symptoms to find the closest matches. The database is populated off-line using solved cases and indexed to allow for efficient matching. Thus problems that occur repeatedly can be easily and automatically resolved without requiring any human problem-solving expertise. We describe a prototype implementation of the system, including the matching algorithm, and present some experimental results demonstrating the value of automatically detecting re-occurrence of the same problem for a popular sofware product.
INDEX TERMS
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CITATION

G. Lohman et al., "Quickly Finding Known Software Problems via Automated Symptom Matching," Autonomic Computing, International Conference on(ICAC), Seattle, Washington, 2005, pp. 101-110.
doi:10.1109/ICAC.2005.49
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