Some months have passed but I finally found the time to set up a test rig for regression testing of my patch under LIVE conditions. I'll describe the setup below.

The good news is, today I found the first bug in my patch (handling of scope=one searches is incorrect). I say "good" news because it shows that the testing setup is doing something right.

In related news, it turns out that apparently the implementation of alias-dereferencing in the hdb backend seems to be faulty, too... not wrt performance, but pureley from a functional point of view. We found a search request which should return around 6700 entries, but only deliveres around 6150. My patched mdb-implementation returns more closely to 6700 entries, but for obvious reasons also that might be wrong still. I had not the time yet to find out what goes wrong in the hdb backend. I'll open a bug if I manage to reproduce it somehow under lab conditions.

My test setup is like this:

I use the productive LDAP content of my company of about 2.4 million Entries, slapcated from the LDAP master, to test against. All user passwd hashes are replaced with a default hash so that the test tool can bind successfully. Slapd configuration is essentially the same as for our productive slaves (esp. the ACLs).

As test cases I use slapd logfiles of our productive clusters (approx 24 million log lines (stats) per server per 24h). Mostly binds and searches. Those are directed against the hdb-configured slapd and a patched-mdb-configured slapd (v 2.4.47). Results are compared: whether binds succeed or fail, and the returned search results. I will extend the tester to also include other operations, but this is waht is relevant to test the patch, I guess.

In the taxonomy of test-methods I would classify this as "advanced monkey testing".

While writing the test scripts I was wondering if somebody else did ever do something similar. There are of course tests in the test directory of the Openldap sources, but are there any (regression) tests made (e.g. for Openldap release candidates) which try to simulate large productive setups?