Yo Joe, This is a really subjective problem that we're trying to tackle. There's not any type of barometer that will be able to tell us how well the Diagnostic Utility is working until we have significant participation from end-users.
I think a good way to implement something like this is to have broad categories for different types of issues. There was a mention of using an md5 hash to map one person's problem to a wiki page. I do not think this is the best solution because it will be too issue-specific. If we imagine each wiki page as a "bucket" and each problem reported as an element which will belong to 1+ buckets, then we can see that when we have 1000 buckets each with 1 element, then it will be really hard to diagnose anything. However, if we have only 100 buckets (meaning broader categories) each with 10 elements, the problem will be (hopefully) easier to detect and fix. Maybe someone with more data mining experience can help out (because I have none), but I think we should break down a reported issue into certain keywords, and use those as a search criteria for the wiki. I think I got off topic...but I like Jason's answer. Thanks, Viet Also, I think this post is related to the topic here too: http://www.nabble.com/exception-handling---first-failure-diagnostic-capture-to15505337.html#a15505337.
