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switch between convex and interior hull, add multiple cores

Signed-off-by: Nikolaj Bjorner <nbjorner@microsoft.com>
This commit is contained in:
Nikolaj Bjorner 2013-08-10 12:21:49 -07:00
parent a20656de35
commit 1c3f715e26
4 changed files with 80 additions and 22 deletions

View file

@ -49,7 +49,8 @@ def_module_params('fixedpoint',
('use_multicore_generalizer', BOOL, False, "PDR: extract multiple cores for blocking states"), ('use_multicore_generalizer', BOOL, False, "PDR: extract multiple cores for blocking states"),
('use_inductive_generalizer', BOOL, True, "PDR: generalize lemmas using induction strengthening"), ('use_inductive_generalizer', BOOL, True, "PDR: generalize lemmas using induction strengthening"),
('use_arith_inductive_generalizer', BOOL, False, "PDR: generalize lemmas using arithmetic heuristics for induction strengthening"), ('use_arith_inductive_generalizer', BOOL, False, "PDR: generalize lemmas using arithmetic heuristics for induction strengthening"),
('use_convex_hull_generalizer', BOOL, False, "PDR: generalize using convex hulls of lemmas"), ('use_convex_closure_generalizer', BOOL, False, "PDR: generalize using convex closures of lemmas"),
('use_convex_interior_generalizer', BOOL, False, "PDR: generalize using convex interiors of lemmas"),
('cache_mode', UINT, 0, "PDR: use no (0), symbolic (1) or explicit cache (2) for model search"), ('cache_mode', UINT, 0, "PDR: use no (0), symbolic (1) or explicit cache (2) for model search"),
('inductive_reachability_check', BOOL, False, "PDR: assume negation of the cube on the previous level when " ('inductive_reachability_check', BOOL, False, "PDR: assume negation of the cube on the previous level when "
"checking for reachability (not only during cube weakening)"), "checking for reachability (not only during cube weakening)"),

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@ -1578,7 +1578,9 @@ namespace pdr {
m_fparams.m_arith_auto_config_simplex = true; m_fparams.m_arith_auto_config_simplex = true;
m_fparams.m_arith_propagate_eqs = false; m_fparams.m_arith_propagate_eqs = false;
m_fparams.m_arith_eager_eq_axioms = false; m_fparams.m_arith_eager_eq_axioms = false;
if (m_params.use_utvpi() && !m_params.use_convex_hull_generalizer()) { if (m_params.use_utvpi() &&
!m_params.use_convex_closure_generalizer() &&
!m_params.use_convex_interior_generalizer()) {
if (classify.is_dl()) { if (classify.is_dl()) {
m_fparams.m_arith_mode = AS_DIFF_LOGIC; m_fparams.m_arith_mode = AS_DIFF_LOGIC;
m_fparams.m_arith_expand_eqs = true; m_fparams.m_arith_expand_eqs = true;
@ -1590,8 +1592,11 @@ namespace pdr {
} }
} }
} }
if (m_params.use_convex_hull_generalizer()) { if (m_params.use_convex_closure_generalizer()) {
m_core_generalizers.push_back(alloc(core_convex_hull_generalizer, *this)); m_core_generalizers.push_back(alloc(core_convex_hull_generalizer, *this, true));
}
if (m_params.use_convex_interior_generalizer()) {
m_core_generalizers.push_back(alloc(core_convex_hull_generalizer, *this, false));
} }
if (!use_mc && m_params.use_inductive_generalizer()) { if (!use_mc && m_params.use_inductive_generalizer()) {
m_core_generalizers.push_back(alloc(core_bool_inductive_generalizer, *this, 0)); m_core_generalizers.push_back(alloc(core_bool_inductive_generalizer, *this, 0));

View file

@ -147,18 +147,23 @@ namespace pdr {
} }
core_convex_hull_generalizer::core_convex_hull_generalizer(context& ctx): core_convex_hull_generalizer::core_convex_hull_generalizer(context& ctx, bool is_closure):
core_generalizer(ctx), core_generalizer(ctx),
m(ctx.get_manager()), m(ctx.get_manager()),
a(m), a(m),
m_sigma(m), m_sigma(m),
m_trail(m) { m_trail(m),
m_is_closure(is_closure) {
m_sigma.push_back(m.mk_fresh_const("sigma", a.mk_real())); m_sigma.push_back(m.mk_fresh_const("sigma", a.mk_real()));
m_sigma.push_back(m.mk_fresh_const("sigma", a.mk_real())); m_sigma.push_back(m.mk_fresh_const("sigma", a.mk_real()));
} }
void core_convex_hull_generalizer::operator()(model_node& n, expr_ref_vector const& core, bool uses_level, cores& new_cores) {
method1(n, core, uses_level, new_cores);
}
void core_convex_hull_generalizer::operator()(model_node& n, expr_ref_vector& core, bool& uses_level) { void core_convex_hull_generalizer::operator()(model_node& n, expr_ref_vector& core, bool& uses_level) {
method1(n, core, uses_level); UNREACHABLE();
} }
// use the entire region as starting point for generalization. // use the entire region as starting point for generalization.
@ -174,20 +179,27 @@ namespace pdr {
// If Constraints & Transition(y0, y) is unsat, then // If Constraints & Transition(y0, y) is unsat, then
// update with new core. // update with new core.
// //
void core_convex_hull_generalizer::method1(model_node& n, expr_ref_vector& core, bool& uses_level) { void core_convex_hull_generalizer::method1(model_node& n, expr_ref_vector const& core, bool uses_level, cores& new_cores) {
manager& pm = n.pt().get_pdr_manager(); manager& pm = n.pt().get_pdr_manager();
expr_ref_vector conv1(m), conv2(m), core1(m), core2(m), eqs(m); expr_ref_vector conv1(m), conv2(m), core1(m), core2(m), eqs(m);
if (core.empty()) { if (core.empty()) {
return; return;
} }
new_cores.push_back(std::make_pair(core, uses_level));
add_variables(n, eqs); add_variables(n, eqs);
if (!mk_convex(core, 0, conv1)) { if (!mk_convex(core, 0, conv1)) {
IF_VERBOSE(0, verbose_stream() << "Non-convex: " << mk_pp(pm.mk_and(core), m) << "\n";); IF_VERBOSE(0, verbose_stream() << "Non-convex: " << mk_pp(pm.mk_and(core), m) << "\n";);
return; return;
} }
conv1.append(eqs); conv1.append(eqs);
conv1.push_back(a.mk_gt(m_sigma[0].get(), a.mk_numeral(rational(0), a.mk_real()))); if (m_is_closure) {
conv1.push_back(a.mk_gt(m_sigma[1].get(), a.mk_numeral(rational(0), a.mk_real()))); conv1.push_back(a.mk_gt(m_sigma[0].get(), a.mk_numeral(rational(0), a.mk_real())));
conv1.push_back(a.mk_gt(m_sigma[1].get(), a.mk_numeral(rational(0), a.mk_real())));
}
else {
conv1.push_back(a.mk_ge(m_sigma[0].get(), a.mk_numeral(rational(0), a.mk_real())));
conv1.push_back(a.mk_ge(m_sigma[1].get(), a.mk_numeral(rational(0), a.mk_real())));
}
conv1.push_back(m.mk_eq(a.mk_numeral(rational(1), a.mk_real()), a.mk_add(m_sigma[0].get(), m_sigma[1].get()))); conv1.push_back(m.mk_eq(a.mk_numeral(rational(1), a.mk_real()), a.mk_add(m_sigma[0].get(), m_sigma[1].get())));
expr_ref fml = n.pt().get_formulas(n.level(), false); expr_ref fml = n.pt().get_formulas(n.level(), false);
expr_ref_vector fmls(m); expr_ref_vector fmls(m);
@ -202,22 +214,23 @@ namespace pdr {
} }
conv2.append(conv1); conv2.append(conv1);
expr_ref state = pm.mk_and(conv2); expr_ref state = pm.mk_and(conv2);
TRACE("pdr", tout << "Check:\n" << mk_pp(state, m) << "\n"; TRACE("pdr",
tout << "New formula:\n" << mk_pp(pm.mk_and(core), m) << "\n"; tout << "Check states:\n" << mk_pp(state, m) << "\n";
tout << "Old formula:\n" << mk_pp(fml, m) << "\n"; tout << "Old states:\n" << mk_pp(fml, m) << "\n";
); );
model_node nd(0, state, n.pt(), n.level()); model_node nd(0, state, n.pt(), n.level());
pred_transformer::scoped_farkas sf(n.pt(), true); pred_transformer::scoped_farkas sf(n.pt(), true);
if (l_false == n.pt().is_reachable(nd, &conv2, uses_level)) { bool uses_level1 = uses_level;
if (l_false == n.pt().is_reachable(nd, &conv2, uses_level1)) {
new_cores.push_back(std::make_pair(conv2, uses_level1));
expr_ref state1 = pm.mk_and(conv2);
TRACE("pdr", TRACE("pdr",
tout << mk_pp(state, m) << "\n"; tout << mk_pp(state, m) << "\n";
tout << "Generalized to:\n" << mk_pp(pm.mk_and(conv2), m) << "\n";); tout << "Generalized to:\n" << mk_pp(state1, m) << "\n";);
IF_VERBOSE(0, IF_VERBOSE(0,
verbose_stream() << mk_pp(state, m) << "\n"; verbose_stream() << mk_pp(state, m) << "\n";
verbose_stream() << "Generalized to:\n" << mk_pp(pm.mk_and(conv2), m) << "\n";); verbose_stream() << "Generalized to:\n" << mk_pp(state1, m) << "\n";);
core.reset();
core.append(conv2);
} }
} }
} }
@ -317,12 +330,47 @@ namespace pdr {
} }
} }
expr_ref core_convex_hull_generalizer::mk_closure(expr* e) {
expr* e0, *e1, *e2;
expr_ref result(m);
if (a.is_lt(e, e1, e2)) {
result = a.mk_le(e1, e2);
}
else if (a.is_gt(e, e1, e2)) {
result = a.mk_ge(e1, e2);
}
else if (m.is_not(e, e0) && a.is_ge(e0, e1, e2)) {
result = a.mk_le(e1, e2);
}
else if (m.is_not(e, e0) && a.is_le(e0, e1, e2)) {
result = a.mk_ge(e1, e2);
}
else if (a.is_ge(e) || a.is_le(e) || m.is_eq(e) ||
(m.is_not(e, e0) && (a.is_gt(e0) || a.is_lt(e0)))) {
result = e;
}
else {
IF_VERBOSE(1, verbose_stream() << "Cannot close: " << mk_pp(e, m) << "\n";);
}
return result;
}
bool core_convex_hull_generalizer::mk_closure(expr_ref_vector& conj) {
for (unsigned i = 0; i < conj.size(); ++i) {
conj[i] = mk_closure(conj[i].get());
if (!conj[i].get()) {
return false;
}
}
return true;
}
bool core_convex_hull_generalizer::mk_convex(expr_ref_vector const& core, unsigned index, expr_ref_vector& conv) { bool core_convex_hull_generalizer::mk_convex(expr_ref_vector const& core, unsigned index, expr_ref_vector& conv) {
conv.reset(); conv.reset();
for (unsigned i = 0; i < core.size(); ++i) { for (unsigned i = 0; i < core.size(); ++i) {
mk_convex(core[i], index, conv); mk_convex(core[i], index, conv);
} }
return !conv.empty(); return !conv.empty() && mk_closure(conv);
} }
void core_convex_hull_generalizer::mk_convex(expr* fml, unsigned index, expr_ref_vector& conv) { void core_convex_hull_generalizer::mk_convex(expr* fml, unsigned index, expr_ref_vector& conv) {

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@ -81,16 +81,20 @@ namespace pdr {
obj_map<func_decl, expr*> m_left; obj_map<func_decl, expr*> m_left;
obj_map<func_decl, expr*> m_right; obj_map<func_decl, expr*> m_right;
obj_map<expr, expr*> m_models; obj_map<expr, expr*> m_models;
bool m_is_closure;
expr_ref mk_closure(expr* e);
bool mk_closure(expr_ref_vector& conj);
bool mk_convex(expr_ref_vector const& core, unsigned index, expr_ref_vector& conv); bool mk_convex(expr_ref_vector const& core, unsigned index, expr_ref_vector& conv);
void mk_convex(expr* fml, unsigned index, expr_ref_vector& conv); void mk_convex(expr* fml, unsigned index, expr_ref_vector& conv);
bool mk_convex(expr* term, unsigned index, bool is_mul, expr_ref& result); bool mk_convex(expr* term, unsigned index, bool is_mul, expr_ref& result);
bool translate(func_decl* fn, unsigned index, expr_ref& result); bool translate(func_decl* fn, unsigned index, expr_ref& result);
void method1(model_node& n, expr_ref_vector& core, bool& uses_level); void method1(model_node& n, expr_ref_vector const& core, bool uses_level, cores& new_cores);
void method2(model_node& n, expr_ref_vector& core, bool& uses_level); void method2(model_node& n, expr_ref_vector& core, bool& uses_level);
void add_variables(model_node& n, expr_ref_vector& eqs); void add_variables(model_node& n, expr_ref_vector& eqs);
public: public:
core_convex_hull_generalizer(context& ctx); core_convex_hull_generalizer(context& ctx, bool is_closure);
virtual ~core_convex_hull_generalizer() {} virtual ~core_convex_hull_generalizer() {}
virtual void operator()(model_node& n, expr_ref_vector const& core, bool uses_level, cores& new_cores);
virtual void operator()(model_node& n, expr_ref_vector& core, bool& uses_level); virtual void operator()(model_node& n, expr_ref_vector& core, bool& uses_level);
}; };