Second International Conference on Autonomic Computing (ICAC'05)
Quickly Finding Known Software Problems via Automated Symptom Matching
Seattle, Washington
June 13-June 16
ISBN: 0-7965-2276-9
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.
Citation:
Mark Brodie, Sheng Ma, Guy Lohman, Laurent Mignet, Natwar Modani, Mark Wilding, Jon Champlin, Peter Sohn, "Quickly Finding Known Software Problems via Automated Symptom Matching," icac, pp.101-110, Second International Conference on Autonomic Computing (ICAC'05), 2005