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Proceedings of IEEE 24th International Symposium on Fault- Tolerant Computing (1994)
Austin, TX, USA
June 15, 1994 to June 17, 1994
ISBN: 0-8186-5520-8
pp: 320-329
I. Lee , Center for Reliable & High Performance Comput., Illinois Univ., Urbana, IL, USA
R.K. Iyer , Center for Reliable & High Performance Comput., Illinois Univ., Urbana, IL, USA
ABSTRACT
This paper presents an approach to automatically identify recurrent software failures using symptoms, in environments where many users run the same software. The approach is based on observations that the majority of field software failures in such environments are recurrences and that failures due to a single fault often share common symptoms. The paper proposes the comparison of failure symptoms, such as stack traces and symptom strings, as a strategy for identifying recurrences. This diagnosis strategy is applied using the actual field software failure data. The results obtained are compared with the diagnosis and repair logs by analysts. Results of such comparisons using the failure, diagnosis, and repair logs in two Tandem system software products show that between 75% and 95% of recurrences can be identified successfully by matching stack traces and symptom strings. Less than 10% of faults are misdiagnosed. These results indicate that automatic identification of recurrences based on their symptoms is possible.<>
INDEX TERMS
software reliability, software maintenance, program testing, software tools
CITATION

I. Lee, R. Iyer and A. Mehta, "Identifying software problems using symptoms," Proceedings of IEEE 24th International Symposium on Fault- Tolerant Computing(FTCS), Austin, TX, USA, 1994, pp. 320-329.
doi:10.1109/FTCS.1994.315628
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