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working on expansion

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Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2012-10-17 08:34:42 -07:00
parent 3a837037d4
commit 8459401b6e
7 changed files with 198 additions and 212 deletions
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78
lib/pdr_generalizers.cpp
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@ -121,10 +121,6 @@ namespace pdr {
TRACE("pdr", tout << "old size: " << old_core_size << " new size: " << core.size() << "\n";);
}
//
// extract multiple cores from unreachable state.
//
void core_multi_generalizer::operator()(model_node& n, expr_ref_vector& core, bool& uses_level) {
UNREACHABLE();
@ -567,78 +563,4 @@ namespace pdr {
uses_level = true;
}
}
//
// cube => n.state() & formula
// so n.state() & cube & ~formula is unsat
// so weaken cube while result is still unsat.
//
void model_farkas_generalizer::operator()(model_node& n, expr_ref_vector& cube) {
ast_manager& m = n.pt().get_manager();
manager& pm = n.pt().get_pdr_manager();
front_end_params& p = m_ctx.get_fparams();
farkas_learner learner(p, m);
expr_ref A0(m), A(m), B(m), state(m);
expr_ref_vector states(m);
A0 = n.pt().get_formulas(n.level(), true);
// extract substitution for next-state variables.
expr_substitution sub(m);
solve_for_next_vars(A0, n, sub);
scoped_ptr<expr_replacer> rep = mk_default_expr_replacer(m);
rep->set_substitution(&sub);
(*rep)(A0);
A0 = m.mk_not(A0);
state = n.state();
(*rep)(state);
datalog::flatten_and(state, states);
ptr_vector<func_decl> preds;
n.pt().find_predecessors(n.model(), preds);
TRACE("pdr", for (unsigned i = 0; i < cube.size(); ++i) tout << mk_pp(cube[i].get(), m) << "\n";);
for (unsigned i = 0; i < preds.size(); ++i) {
pred_transformer& pt = m_ctx.get_pred_transformer(preds[i]);
SASSERT(pt.head() == preds[i]);
expr_ref_vector lemmas(m), o_cube(m), other(m), o_state(m), other_state(m);
pm.partition_o_atoms(cube, o_cube, other, i);
pm.partition_o_atoms(states, o_state, other_state, i);
TRACE("pdr",
tout << "cube:\n";
for (unsigned i = 0; i < cube.size(); ++i) tout << mk_pp(cube[i].get(), m) << "\n";
tout << "o_cube:\n";
for (unsigned i = 0; i < o_cube.size(); ++i) tout << mk_pp(o_cube[i].get(), m) << "\n";
tout << "other:\n";
for (unsigned i = 0; i < other.size(); ++i) tout << mk_pp(other[i].get(), m) << "\n";
tout << "o_state:\n";
for (unsigned i = 0; i < o_state.size(); ++i) tout << mk_pp(o_state[i].get(), m) << "\n";
tout << "other_state:\n";
for (unsigned i = 0; i < other_state.size(); ++i) tout << mk_pp(other_state[i].get(), m) << "\n";
);
A = m.mk_and(A0, pm.mk_and(other), pm.mk_and(other_state));
B = m.mk_and(pm.mk_and(o_cube), pm.mk_and(o_state));
TRACE("pdr",
tout << "A: " << mk_pp(A, m) << "\n";
tout << "B: " << mk_pp(B, m) << "\n";);
if (learner.get_lemma_guesses(A, B, lemmas)) {
cube.append(lemmas);
cube.append(o_state);
TRACE("pdr",
tout << "New lemmas:\n";
for (unsigned i = 0; i < lemmas.size(); ++i) {
tout << mk_pp(lemmas[i].get(), m) << "\n";
}
);
}
}
TRACE("pdr", for (unsigned i = 0; i < cube.size(); ++i) tout << mk_pp(cube[i].get(), m) << "\n";);
}
};