Diagnosing rediscovered software problems using symptoms

This paper presents an approach to automatically diagnosing rediscovered software failures using symptoms, in environments in which many users run the same procedural software system. The approach is based on the observation that the great majority of field software failures are rediscoveries of previously reported problems and that failures caused by the same defect often share common symptoms. Based on actual data, the paper develops a small software failure fingerprint, which consists of the procedure call trace, problem detection location, and the identification of the executing software. The paper demonstrates that over 60 percent of rediscoveries can be automatically diagnosed based on fingerprints; less than 10 percent of defects are misdiagnosed. The paper also discusses a pilot that implements the approach. Using the approach not only saves service resources by eliminating repeated data collection for and diagnosis of reoccurring problems, but it can also improve service response time for rediscoveries.