I don't know if this has come up yet but....
In terms of tagging errors we might be able to use some machine
learning techniques.
There are NLP/learning systems that interpret logs. They learn over
time what is normal and what isn't and can flag things that are
abnormal.
For example, people are using support vector machines (SVM) analysis
on log files to do intrusion detection. Here's a link for intrusion
detection called Robust Anomaly Detection Using Support Vector
Machines http://wwwcsif.cs.ucdavis.edu/~liaoy/research/
RSVM_Anomaly_journal.pdf
This paper from IBM gives some more background information on how
such a thing might work. http://www.research.ibm.com/journal/sj/413/
johnson.html
I have previously used an open source toolkit from CMU called rainbow
to do these types of analysis.
-arturo
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