chore: Split out the finishing tactic aspect of simp_mem into mem_omega [2/?] #231
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We also change mem_omega to be less agressive by default, and only exploiting PairwiseSeparate hypotheses if asked to by the user with mem_omega!.
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…ga [2/?] This helps control how aggressive simp_mem is. I was hoping that we would see a major performance difference. We do see some evidence for improvement in the `Experiments/MemoryAliasing.lean` (the numbers are extremely consistent across runs: ``` lake build Proofs.Experiments.MemoryAliasing 2.86s user 0.34s system 92% cpu 3.466 total lake build Proofs.Experiments.MemoryAliasing 2.76s user 0.33s system 92% cpu 3.332 total ``` --- However, on the much larger `Memcpy.lean`, these types of considerations seem to just not matter: ``` lake build Proofs.Experiments.Memcpy.MemCpyVCG 31.79s user 0.81s system 99% cpu 32.878 total lake build Proofs.Experiments.Memcpy.MemCpyVCG 32.79s user 0.80s system 99% cpu 33.870 total ``` This is a tad disappointing, but such is life. Onward to the next refactor. This is stacked on top of #230
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### Description: This allows us to gradually convert all our tactics to `MetaM`, which provides the correct level to discipline to make sure that bugs like #154 don't happen anymore. Also, as a mild bonus, one hopes that eliminating `evalTactic` makes stuff a bit faster, but I would not hold my breath on this. Stacked on #231 ### Testing: What tests have been run? Did `make all` succeed for your changes? Was conformance testing successful on an Aarch64 machine? ### License: By submitting this pull request, I confirm that my contribution is made under the terms of the Apache 2.0 license.
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This helps control how aggressive
simp_memis, sincesimp_memnow no longer closes memory goals, but rather expects the user to manually invokemem_omegawhen necessary. Another impact of this change is that we splitmem_omegainto two tactics:mem_omegathat does not exposepairwiseSeparategoals, andmem_omega!, which does. This also helps control the performance ofmem_omega, and hopefully, this ensures that the user is careful before exposing a fullO(n^2)set of constraints to the user.I was hoping that we would see a major performance difference. We do see some evidence for improvement in the
Experiments/MemoryAliasing.lean(the numbers are extremely consistent across runs:However, on the much larger
Memcpy.lean, these types of considerations seem to just not matter:This is a tad disappointing, but such is life. Onward to the next refactor. This is stacked on top of #230