On 7/25/2013 6:56 PM, Christian Heimes wrote:
Am 26.07.2013 00:32, schrieb Terry Reedy:
# Since false positives should stay constant as true positives are
reduced toward 0, false / all should tend toward 1 (100%) if I
understand the ratio correctly.
Which I did not ;-).
About 40% of the dismissed cases are cause by a handful of issues. I
have documented these issues as "known limitations"
http://docs.python.org/devguide/coverity.html#known-limitations .
For example about 35 false positives are related to PyLong_FromLong()
and our small integer optimization. A correct modeling file would
eliminate the false positive defects. My attempts don't work as hoped
and I don't have access to all professional coverity tools to debug my
trials.
Perhaps Coverity will help when doing an audit.
Nearly 20 false positives are caused by Py_BuildValue("N"). I'm still
astonished that Coverity understands Python's reference counting most of
the time. :)
Did I mention that we have almost reached Level 3? All major defects
It is hard to measure the benefit of preventitive medicine, but I
imagine that we should see fewer mysterious crashes and heisenbugs than
we would have. In any case, Level 3 certification should help people
promoting the use of Python in organizational settings, whether as
employees or consultants.
have been dealt with (one of them locally on the test machine until
Larry pushes his patch soonish), 4 of 7 minor issues must be closed and
.1 * 390 allows 3 defects (or 4 if they round up) -- astonishingly good!
our dismissed rate is just little over 20% (222 out of 1054 = 21%).
So merely verifying the 35 PyLong_FromLong dismissals will put us under.
Thanks for clarifying the proper denominator -- all defects ever found.
It seems obvious in retrospect, but I was focused on current stats, not
the history.
--
Terry Jan Reedy
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