feat(Test): computational graph invariants, prove 25 tests#3660
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XC0R wants to merge 1 commit intogoogle-deepmind:mainfrom
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feat(Test): computational graph invariants, prove 25 tests#3660XC0R wants to merge 1 commit intogoogle-deepmind:mainfrom
XC0R wants to merge 1 commit intogoogle-deepmind:mainfrom
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For all these graph tests, might it be better to implement computational variants of the definitions of the graph properties and then prove once and for all graphs that the computational variants are equivalent? |
Add computable variants (BFS distance, powerset-based independence/domination numbers, Wiener/Szeged indices) to Definitions.lean with equivalence theorems in Invariants.lean. Refactor graph test proofs for 5 invariants across all 5 graphs to use 'rw [equiv]; decide +native' per google-deepmind#3676 approach. Supersedes google-deepmind#3659, google-deepmind#3658.
XC0R
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This was referenced Apr 4, 2026
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Summary
Implements computational variants of graph property definitions (per the approach suggested in #3676) and uses them to prove 25 test theorems across all 5 graphs.
Definitions.lean: BFS-based
computable_dist, powerset-basedcomputable_indep_num,computable_dom_num,computable_wiener,computable_avg_dist,computable_szeged_aux,computable_szeged_indexInvariants.lean: 6 equivalence theorems linking noncomputable spec definitions to computable variants
Test.lean: 25 theorems proved via
rw [equiv]; decide +nativeTheorems proved (5 invariants × 5 graphs)
Supersedes #3659, #3658.
Notes