(1) in a practical sense there is basically no value. BPSW is extremely fast (M-R base 2 plus strong Lucas) and there are no known counterexamples after 38 years of use. It's what is used by Pari/GP, Mathematica, etc. You can add a few more M-R tests to reduce the chance even further (as FIPS 186-4 recommends for crypto use).
(2) crypto *programs* are almost all written by programmers, not mathematicians. Most of them have never heard of anything beyond Miller-Rabin.
(3) Coding Miller-Rabin is quite simple. It's 10-25 lines of code, and written in hundreds of books. It's fairly easy to write correctly, and easy for others to double check. Coding APR-CL or ECPP is quite difficult. Open source implementations for both are over 1000 lines, and verifying that they actually work is difficult. ECPP can give a primality certificate that can be verified so that is helpful, but there are still many more areas to screw something up. A working and solid probable primality test is *more* certain than a badly coded primality proof implementation.
I sure hope so. I've argued this to various languages and libraries for a few years, and mostly they don't really care, other than they've heard of M-R and not of anything else.
One bottleneck I ran into are the "Prove that the probability is smaller" argument. The probability bound for BPSW is actually not very good, but empirically we see that bound is grotesquely conservative. One can always add more random-base M-R tests if desired.
There is also the problem that statistical thinking is hard for people. This comes up with using fixed bases and not grasping that this ruins the "2^-80 probability!" (for example) claim. That only applies to a random input.