mirror of
https://github.com/Z3Prover/z3
synced 2025-04-23 17:15:31 +00:00
Fix some spelling errors (mostly in comments).
This commit is contained in:
parent
880ce12e2d
commit
326bf401b9
121 changed files with 205 additions and 205 deletions
|
@ -615,7 +615,7 @@ namespace datalog {
|
|||
|
||||
void ensure_engine();
|
||||
|
||||
// auxilary functions for SMT2 pretty-printer.
|
||||
// auxiliary functions for SMT2 pretty-printer.
|
||||
void declare_vars(expr_ref_vector& rules, mk_fresh_name& mk_fresh, std::ostream& out);
|
||||
|
||||
//undefined and private copy constructor and operator=
|
||||
|
|
|
@ -110,7 +110,7 @@ namespace datalog {
|
|||
/**
|
||||
\brief Manager for the \c rule class
|
||||
|
||||
\remark \c rule_manager objects are interchangable as long as they
|
||||
\remark \c rule_manager objects are interchangeable as long as they
|
||||
contain the same \c ast_manager object.
|
||||
*/
|
||||
class rule_manager
|
||||
|
|
|
@ -97,7 +97,7 @@ namespace datalog {
|
|||
\brief Auxiliary function used to create a tail based on \c pred for a new rule.
|
||||
The variables in \c pred are re-assigned using \c next_idx and \c varidx2var.
|
||||
A variable is considered non-local to the rule if it is in the set \c non_local_vars.
|
||||
Non-local variables are coppied to new_rule_args, and their sorts to \c new_rule_domain.
|
||||
Non-local variables are copied to new_rule_args, and their sorts to \c new_rule_domain.
|
||||
The new predicate is stored in \c new_pred.
|
||||
*/
|
||||
void mk_new_rule_tail(ast_manager & m, app * pred,
|
||||
|
|
|
@ -143,8 +143,8 @@ def_module_params('fp',
|
|||
('spacer.native_mbp', BOOL, True, "Use native mbp of Z3"),
|
||||
('spacer.eq_prop', BOOL, True, "Enable equality and bound propagation in arithmetic"),
|
||||
('spacer.weak_abs', BOOL, True, "Weak abstraction"),
|
||||
('spacer.restarts', BOOL, False, "Enable reseting obligation queue"),
|
||||
('spacer.restart_initial_threshold', UINT, 10, "Intial threshold for restarts"),
|
||||
('spacer.restarts', BOOL, False, "Enable resetting obligation queue"),
|
||||
('spacer.restart_initial_threshold', UINT, 10, "Initial threshold for restarts"),
|
||||
('spacer.random_seed', UINT, 0, "Random seed to be used by SMT solver"),
|
||||
|
||||
('spacer.mbqi', BOOL, True, 'Enable mbqi'),
|
||||
|
|
|
@ -11,7 +11,7 @@ Copyright (c) 2015 Microsoft Corporation
|
|||
|
||||
Abstract:
|
||||
|
||||
Horn normal form convertion.
|
||||
Horn normal form conversion.
|
||||
|
||||
Author:
|
||||
|
||||
|
|
|
@ -332,7 +332,7 @@ namespace datalog {
|
|||
|
||||
|
||||
void internalize() {
|
||||
// populate maps (should be bit-sets) of decendants.
|
||||
// populate maps (should be bit-sets) of descendants.
|
||||
if (m_internalized) {
|
||||
return;
|
||||
}
|
||||
|
|
|
@ -120,7 +120,7 @@ public:
|
|||
|
||||
This operation invalidates the line previously retrieved.
|
||||
|
||||
This operatio can be called only if we are not at the end of file.
|
||||
This operation can be called only if we are not at the end of file.
|
||||
|
||||
User is free to modify the content of the returned array until the terminating NULL character.
|
||||
*/
|
||||
|
@ -876,7 +876,7 @@ protected:
|
|||
|
||||
/**
|
||||
\brief Parse predicate arguments. If \c f==0, they are arguments of a predicate declaration.
|
||||
If parsing a declaration, argumens names are pushed to the \c arg_names vector.
|
||||
If parsing a declaration, argument names are pushed to the \c arg_names vector.
|
||||
*/
|
||||
dtoken parse_args(dtoken tok, func_decl* f, expr_ref_vector& args, svector<symbol> & arg_names) {
|
||||
if (tok != TK_LP) {
|
||||
|
|
|
@ -295,7 +295,7 @@ namespace datalog {
|
|||
Precondition: &orig.get_plugin()==this
|
||||
*/
|
||||
virtual base_object * mk_empty(const signature & s, family_id kind) {
|
||||
SASSERT(kind==get_kind()); //if plugin uses multiple kinds, this function needs to be overriden
|
||||
SASSERT(kind==get_kind()); //if plugin uses multiple kinds, this function needs to be overridden
|
||||
return mk_empty(s);
|
||||
}
|
||||
|
||||
|
|
|
@ -1319,7 +1319,7 @@ namespace datalog {
|
|||
|
||||
if(!m_table_cond_columns.empty()) {
|
||||
//We will keep the table variables that appear in the condition together
|
||||
//with the index column and then iterate throught the tuples, evaluating
|
||||
//with the index column and then iterate through the tuples, evaluating
|
||||
//the rest of the condition on the inner relations.
|
||||
unsigned_vector removed_cols;
|
||||
unsigned table_data_col_cnt = r.m_table_sig.size()-1;
|
||||
|
|
|
@ -640,7 +640,7 @@ namespace datalog {
|
|||
reg_idx m_src;
|
||||
reg_idx m_tgt;
|
||||
reg_idx m_delta;
|
||||
bool m_widen; //if true, widening is performed intead of an union
|
||||
bool m_widen; //if true, widening is performed instead of an union
|
||||
public:
|
||||
instr_union(reg_idx src, reg_idx tgt, reg_idx delta, bool widen)
|
||||
: m_src(src), m_tgt(tgt), m_delta(delta), m_widen(widen) {}
|
||||
|
|
|
@ -253,7 +253,7 @@ namespace datalog {
|
|||
\brief Return functor that transforms a table into one that lacks columns listed in
|
||||
\c removed_cols array.
|
||||
|
||||
The \c removed_cols cotains columns of table \c t in strictly ascending order.
|
||||
The \c removed_cols contains columns of table \c t in strictly ascending order.
|
||||
*/
|
||||
relation_transformer_fn * mk_project_fn(const relation_base & t, unsigned col_cnt,
|
||||
const unsigned * removed_cols);
|
||||
|
@ -420,7 +420,7 @@ namespace datalog {
|
|||
\brief Return functor that transforms a table into one that lacks columns listed in
|
||||
\c removed_cols array.
|
||||
|
||||
The \c removed_cols cotains columns of table \c t in strictly ascending order.
|
||||
The \c removed_cols contains columns of table \c t in strictly ascending order.
|
||||
|
||||
If a project operation removes a non-functional column, all functional columns become
|
||||
non-functional (so that none of the values in functional columns are lost)
|
||||
|
|
|
@ -568,7 +568,7 @@ namespace datalog {
|
|||
}
|
||||
|
||||
/**
|
||||
In this function we modify the content of table functional columns without reseting indexes.
|
||||
In this function we modify the content of table functional columns without resetting indexes.
|
||||
This is ok as long as we do not allow indexing on functional columns.
|
||||
*/
|
||||
void sparse_table::ensure_fact(const table_fact & f) {
|
||||
|
|
|
@ -85,7 +85,7 @@ namespace datalog {
|
|||
/**
|
||||
\brief Restrict the set of used predicates to \c res.
|
||||
|
||||
The function deallocates unsused relations, it does not deal with rules.
|
||||
The function deallocates unused relations, it does not deal with rules.
|
||||
*/
|
||||
void restrict_predicates(func_decl_set const& predicates) override;
|
||||
|
||||
|
|
|
@ -7,8 +7,8 @@ Module Name:
|
|||
|
||||
Abstract:
|
||||
|
||||
Proviced abstract interface and some inplementations of algorithms
|
||||
for strenghtning lemmas
|
||||
Provides abstract interface and some implementations of algorithms
|
||||
for strenghtening lemmas
|
||||
|
||||
Author:
|
||||
|
||||
|
@ -161,7 +161,7 @@ bool farkas_learner::is_pure_expr(func_decl_set const& symbs, expr* e, ast_manag
|
|||
in a clausal version.
|
||||
|
||||
NB: the routine is not interpolating, though an interpolating variant would
|
||||
be preferrable because then we can also use it for model propagation.
|
||||
be preferable because then we can also use it for model propagation.
|
||||
|
||||
We collect the unit derivable nodes from bs.
|
||||
These are the weakenings of bs, besides the
|
||||
|
|
|
@ -186,7 +186,7 @@ void lemma_quantifier_generalizer::find_candidates(expr *e,
|
|||
|
||||
std::sort(candidates.c_ptr(), candidates.c_ptr() + candidates.size(),
|
||||
index_lt_proc(m));
|
||||
// keep actual select indecies in the order found at the back of
|
||||
// keep actual select indices in the order found at the back of
|
||||
// candidate list. There is no particular reason for this order
|
||||
candidates.append(extra);
|
||||
}
|
||||
|
@ -199,24 +199,24 @@ bool lemma_quantifier_generalizer::match_sk_idx(expr *e, app_ref_vector const &z
|
|||
contains_app has_zk(m, zks.get(0));
|
||||
|
||||
if (!contains_selects(e, m)) return false;
|
||||
app_ref_vector indicies(m);
|
||||
get_select_indices(e, indicies);
|
||||
if (indicies.size() > 2) return false;
|
||||
app_ref_vector indices(m);
|
||||
get_select_indices(e, indices);
|
||||
if (indices.size() > 2) return false;
|
||||
|
||||
unsigned i=0;
|
||||
if (indicies.size() == 1) {
|
||||
if (!has_zk(indicies.get(0))) return false;
|
||||
if (indices.size() == 1) {
|
||||
if (!has_zk(indices.get(0))) return false;
|
||||
}
|
||||
else {
|
||||
if (has_zk(indicies.get(0)) && !has_zk(indicies.get(1)))
|
||||
if (has_zk(indices.get(0)) && !has_zk(indices.get(1)))
|
||||
i = 0;
|
||||
else if (!has_zk(indicies.get(0)) && has_zk(indicies.get(1)))
|
||||
else if (!has_zk(indices.get(0)) && has_zk(indices.get(1)))
|
||||
i = 1;
|
||||
else if (!has_zk(indicies.get(0)) && !has_zk(indicies.get(1)))
|
||||
else if (!has_zk(indices.get(0)) && !has_zk(indices.get(1)))
|
||||
return false;
|
||||
}
|
||||
|
||||
idx = indicies.get(i);
|
||||
idx = indices.get(i);
|
||||
sk = zks.get(0);
|
||||
return true;
|
||||
}
|
||||
|
|
|
@ -124,7 +124,7 @@ namespace spacer {
|
|||
* We can rewrite (E2) to rewrite (E1) to
|
||||
* (BP*Fark(BP)) => (neg(A*Fark(A) + BNP*Fark(BNP) + (neg D)*Fark(D))) (E3)
|
||||
* and since we can derive (A*Fark(A) + BNP*Fark(BNP) + (neg D)*Fark(D)) from
|
||||
* A, BNP and D, we also know that it is inconsisent. Therefore
|
||||
* A, BNP and D, we also know that it is inconsistent. Therefore
|
||||
* neg(A*Fark(A) + BNP*Fark(BNP) + (neg D)*Fark(D)) is a solution.
|
||||
*
|
||||
* Finally we also need the following workaround:
|
||||
|
|
|
@ -1097,7 +1097,7 @@ namespace tb {
|
|||
m_S1.apply(2, delta, expr_offset(src.get_constraint(), 1), tmp2);
|
||||
constraint = m.mk_and(tmp, tmp2);
|
||||
|
||||
// perform trival quantifier-elimination:
|
||||
// perform trivial quantifier-elimination:
|
||||
uint_set index_set;
|
||||
expr_free_vars fv;
|
||||
fv(head);
|
||||
|
|
|
@ -280,7 +280,7 @@ namespace datalog {
|
|||
}
|
||||
}
|
||||
|
||||
// model convertion: identity function.
|
||||
// model conversion: identity function.
|
||||
|
||||
if (instantiated) {
|
||||
result->inherit_predicates(source);
|
||||
|
|
|
@ -45,7 +45,7 @@ namespace datalog {
|
|||
|
||||
unsigned pt_len = r->get_positive_tail_size();
|
||||
if(pt_len != r->get_uninterpreted_tail_size()) {
|
||||
// we dont' expect rules with negative tails to be total
|
||||
// we don't expect rules with negative tails to be total
|
||||
return false;
|
||||
}
|
||||
|
||||
|
@ -97,7 +97,7 @@ namespace datalog {
|
|||
void mk_subsumption_checker::scan_for_total_rules(const rule_set & rules) {
|
||||
bool new_discovered;
|
||||
//we cycle through the rules until we keep discovering new total relations
|
||||
//(discovering a total relation migh reveal other total relations)
|
||||
//(discovering a total relation might reveal other total relations)
|
||||
do {
|
||||
new_discovered = false;
|
||||
rule_set::iterator rend = rules.end();
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue