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Recognition of error symptoms in large systemsA methodology for automatically detecting symptoms of frequently occurring errors in large computer systems is developed. The proposed symptom recognition methodology and its validation are based on probabilistic techniques. The technique is shown to work on real failure data from two CYBER systems at the University of Illinois. The methodology allows for the resolution between independent and dependent causes and, also quantifies a measure of the strength of relationship among errors. Comparison made with failure/repair information obtained from field maintenance engineers shows that in 85% of the cases, the error symptoms recognized by our approach correspond to real system problems. Further, the remaining 15% although not directly supported by field data, were confirmed as valid problems. Some of these were shown to be persistent problems which otherwise would have been considered as minor transients and hence ignored.
Document ID
19940003671
Acquisition Source
Legacy CDMS
Document Type
Other
Authors
Iyer, Ravishankar K.
(Illinois Univ. Urbana-Champaign, IL, United States)
Sridhar, V.
(Illinois Univ. Urbana-Champaign, IL, United States)
Date Acquired
August 16, 2013
Publication Date
November 17, 1987
Publication Information
Publication: Presentation Slides and Publications. NASA Review of ICLASS: Illinois Computer Laboratory for Aerospace Systems and Software
Subject Category
Computer Systems
Meeting Information
Meeting: Conference of the 1986 Proceedings Fall Joint Computer
Location: Dallas, TX
Country: United States
Start Date: November 2, 1986
End Date: November 6, 1986
Accession Number
94N70426
Funding Number(s)
CONTRACT_GRANT: N00014-84-C-0149
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
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