int main()
{
Verifier v;
string fileName;
cout << "Sudoku Verifier\n";
for (int i = 1; i <= NUM_FILES; i++)
{
cout << endl;
// Construct file pathname
fileName = string("testpuzzle")
+ (char)('0' + i) + ".txt";
// Read the solution file as input
v.readGrid(fileName.c_str());
// Print the Sudoku grid
v.printGrid();
// Verify whether or not the solution is correct
if (v.verifySolution())
cout << "\nThis is a valid Sudoku solution\n";
else
cout << "\nThis is not a valid Sudoku solution\n";
}
system("pause");
return 0;
}
int main(int argc, char **argv)
{
#if doMPI
if ( MPI_SUCCESS != MPI_Init( & argc , & argv ) ) {
std::cerr << "MPI_Init FAILED" << std::endl ;
std::abort();
}
#endif
Verifier vf;
vf.verify(argc, argv);
#if doMPI
#endif
// MPI_Finalize();
return 0;
}
void VNS::run() {
const ProcessCount pCount = instance().processes().size();
// read configuration
const uint32_t kMin = hasParam("kMin") ? param<uint32_t>("kMin") : 2;
const uint32_t kMax = hasParam("kMax") ? param<uint32_t>("kMax") : 5;
const uint32_t trials = hasParam("trials") ? param<uint32_t>("trials") : 5;
const uint32_t maxInf = hasParam("maxInf") ? param<uint32_t>("maxInf") : 3;
m_maxTrialsLS = param<uint64_t>("maxTrialsLS", defaultMaxTrialsLS());
m_maxSamplesLS = param<uint64_t>("maxSamplesLS", pCount);
// initialize RNG
m_rng.seed(seed());
// initialize shaker
SmartShaker shaker(trials, maxInf);
shaker.init(instance(), initial(), seed(), flag());
// initialize solution info
m_current.reset(new SolutionInfo(instance(), initial()));
// run local search to get starting solution
localSearch();
// set best and publish to pool
m_best = std::move(m_current);
pool().push(m_best->objective(), m_best->solution());
// start VNS
uint64_t it = 0;
uint32_t k = kMin;
uint64_t syncPeriod = 100;
uint64_t diversifyPeriod = 100;
uint64_t concentratePeriod = 100;
#ifdef CHECK_VNS
Verifier v;
#endif
while (!interrupted()) {
++it;
// periodically sync with best result
if (it % syncPeriod == 0) {
SolutionPool::Entry entry;
if (pool().best(entry)) {
if (entry.obj() < m_best->objective()) {
m_best.reset(new SolutionInfo(instance(), initial(), *(entry.ptr())));
k = kMin;
}
}
}
// periodically start from a good solution different from the best known one
if (it % diversifyPeriod == 25) {
SolutionPool::Entry hdEntry;
if (pool().randomHighDiversity(hdEntry)) {
m_current.reset(new SolutionInfo(instance(), initial(), *hdEntry.ptr()));
}
} else if (it % concentratePeriod == 75) {
SolutionPool::Entry hqEntry;
if (pool().randomHighQuality(hqEntry)) {
m_current.reset(new SolutionInfo(instance(), initial(), *hqEntry.ptr()));
}
} else {
// most of the times start from the best known solution
m_current.reset(new SolutionInfo(*m_best));
}
// make random jump
shaker.shake(k, *m_current);
// since shaking might take a long time, check for interruption
if (interrupted()) {
#ifdef TRACE_VNS
std::cout << "VNS - Interrupted during shake @ iteration " << it << std::endl;
#endif
break;
}
#ifdef CHECK_VNS
// verify shaking led to a feasible solution
if (!v.verify(instance(), initial(), m_current->solution()).feasible()) {
throw std::runtime_error("VNS - Shaking lead to an unfeasible solution");
}
#endif
// do a local search
localSearch();
#ifdef CHECK_VNS
// verify shaking led to a feasible solution
if (!v.verify(instance(), initial(), m_current->solution()).feasible()) {
throw std::runtime_error("VNS - Local search lead to an unfeasible solution");
}
#endif
// update best solution if improved if needed
if (m_current->objective() < m_best->objective()) {
m_best = std::move(m_current);
#ifdef TRACE_VNS
std::cout << "VNS - Improvement found @ iteration " << it << ": " << m_best->objective() << std::endl;
#endif
pool().push(m_best->objective(), m_best->solution());
// restart from small neighborhood
k = kMin;
} else {
// move to another neighborhood
k = kMin + (k - kMin + 1) % (kMax - kMin + 1);
}
}
#ifdef TRACE_VNS
std::cout << "VNS - Completed after " << it << " iterations" << std::endl;
std::cout << "VNS - Failures per shake " << shaker.failuresPerShake() << std::endl;
#endif
signalCompletion();
}
int main(int argc, char** argv) {
Galois::StatManager statManager;
LonestarStart(argc, argv, name, desc, url);
graph = new Graph();
{
Mesh m;
m.read(graph, filename.c_str(), detAlgo == nondet);
Verifier v;
if (!skipVerify && !v.verify(graph)) {
std::cerr << "bad input mesh\n";
assert(0 && "Refinement failed");
abort();
}
}
std::cout << "configuration: " << std::distance(graph->begin(), graph->end())
<< " total triangles, " << std::count_if(graph->begin(), graph->end(), is_bad(graph)) << " bad triangles\n";
Galois::Statistic("MeminfoPre1", GaloisRuntime::MM::pageAllocInfo());
Galois::preAlloc(15 * numThreads + GaloisRuntime::MM::pageAllocInfo() * 10);
Galois::Statistic("MeminfoPre2", GaloisRuntime::MM::pageAllocInfo());
Galois::StatTimer T;
T.start();
if (detAlgo == nondet)
Galois::do_all_local(*graph, Preprocess());
else
std::for_each(graph->begin(), graph->end(), Preprocess());
Galois::Statistic("MeminfoMid", GaloisRuntime::MM::pageAllocInfo());
Galois::StatTimer Trefine("refine");
Trefine.start();
using namespace GaloisRuntime::WorkList;
typedef LocalQueues<dChunkedLIFO<256>, ChunkedLIFO<256> > BQ;
typedef ChunkedAdaptor<false,32> CA;
switch (detAlgo) {
case nondet:
Galois::for_each_local<CA>(wl, Process<>()); break;
case detBase:
Galois::for_each_det(wl.begin(), wl.end(), Process<>()); break;
case detPrefix:
Galois::for_each_det(wl.begin(), wl.end(), Process<detPrefix>(), Process<>());
break;
case detDisjoint:
Galois::for_each_det(wl.begin(), wl.end(), Process<detDisjoint>()); break;
default: std::cerr << "Unknown algorithm" << detAlgo << "\n"; abort();
}
Trefine.stop();
T.stop();
Galois::Statistic("MeminfoPost", GaloisRuntime::MM::pageAllocInfo());
if (!skipVerify) {
int size = Galois::ParallelSTL::count_if(graph->begin(), graph->end(), is_bad(graph));
if (size != 0) {
std::cerr << size << " bad triangles remaining.\n";
assert(0 && "Refinement failed");
abort();
}
Verifier v;
if (!v.verify(graph)) {
std::cerr << "Refinement failed.\n";
assert(0 && "Refinement failed");
abort();
}
std::cout << "Refinement OK\n";
}
return 0;
}
bool Generalization::EvaluateRisk( const vector<long>& rVecAttr, Verifier& rVerifier )
{
try
{
AnonyException temp_exception;
temp_exception.m_bShallContinue = true;
stringstream temp_sstream;
if (rVecAttr.size() > m_vecQiAttr.size())
{
temp_sstream << "Generalization::EvaluateRisk Error: Incorrect number of attributes";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
vector<long> vec_attr = rVecAttr;
sort( vec_attr.begin(), vec_attr.end() );
long i, j;
j = 0;
for (i = 0; i < vec_attr.size(); ++i)
{
while (m_vecQiAttr[j].m_nAttr < vec_attr[i] && m_vecQiAttr[j].m_nAttr != vec_attr[i])
{
++j;
if (j == m_vecQiAttr.size())
{
temp_sstream << "Generalization::EvaluateRisk Error: Input attributes are not all quasi-identifiers";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
}
}
const vector<Metadata>& r_meta = m_pMicrodata->GetVecMeta();
const vector<UnitValue>& r_micro = m_pMicrodata->GetVecTuple();
const long attr_num = r_meta.size();
const long tuple_num = r_micro.size() / attr_num;
const long qi_num = m_vecQiAttr.size();
m_vecRisk.clear();
m_vecRisk.insert( m_vecRisk.end(), tuple_num, 0 );
list<EqvClass>::iterator eqv_pos;
list<long>::const_iterator tpl_pos;
if (rVecAttr.size() == m_vecQiAttr.size())
{
vector<EqvClass*> vec_pt_eqv;
vec_pt_eqv.push_back( NULL );
for (eqv_pos = m_lstEqvClass.begin(); eqv_pos != m_lstEqvClass.end(); ++eqv_pos)
{
vec_pt_eqv[0] = &(*eqv_pos);
rVerifier.SetRisk( vec_pt_eqv, m_vecRisk );
}
}
else
{
pair< vector<UnitValue>, vector<EqvClass*> > key_pair;
key_pair.first.insert( key_pair.first.end(), rVecAttr.size(), UnitValue() );
map<vector< UnitValue>, vector<EqvClass*> > emap;
map<vector< UnitValue>, vector<EqvClass*> >::iterator emap_pos;
vector<map< vector<UnitValue>, vector<EqvClass*> >::iterator> vec_pos;
vec_pos.reserve( m_lstEqvClass.size() );
pair< map<vector<UnitValue>, vector<EqvClass*> >::iterator, bool> rslt_pair;
map<UnitValue, long>::iterator sv_pos;
for (eqv_pos = m_lstEqvClass.begin(); eqv_pos != m_lstEqvClass.end(); ++eqv_pos)
{
EqvClass& r_eqv = *eqv_pos;
for (j = 0; j < rVecAttr.size(); ++j)
{
if (r_eqv.m_vecNodePos[rVecAttr[j]] != -1)
{
key_pair.first[j] = r_eqv.m_vecNodePos[rVecAttr[j]];
}
else
{
key_pair.first[j] = r_micro[r_eqv.m_lstTplId.front() * attr_num + rVecAttr[j]];
}
}
emap_pos = emap.find( key_pair.first );
if (emap_pos == emap.end())
{
rslt_pair = emap.insert( key_pair );
(*rslt_pair.first).second.push_back( &r_eqv );
vec_pos.push_back( rslt_pair.first );
}
else
{
(*emap_pos).second.push_back( &r_eqv );
}
}
for (emap_pos = emap.begin(); emap_pos != emap.end(); ++emap_pos)
{
rVerifier.SetRisk( (*emap_pos).second, m_vecRisk );
}
}
for (i = 0; i < tuple_num; ++i)
{
if (m_vecStatus[i] != anony::NORMAL)
{
m_vecRisk[i] = 0;
}
}
}
catch( AnonyException e )
{
m_vecRisk.clear();
cout << e.GetMsg() << endl;
throw( e );
}
return true;
}
bool Generalization::Anonymize( Verifier& rVerifier )
{
try
{
AnonyException temp_exception;
temp_exception.m_bShallContinue = true;
stringstream temp_sstream;
if (m_pMicrodata == NULL)
{
temp_sstream << "Generalization::Anonymize Error: Pointer to the microdata is NULL";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
if (m_eqvRootClass.m_lstTplId.size() == 0)
{
temp_sstream << "Generalization::Anonymize Error: Root equivalence class has not been initialized";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
// Check whether the tuples in the "root" equivalence class need to be reloaded or not
if (m_bRootDirty == true)
{
InitRootClass();
m_bRootDirty = false;
}
long i, j, k;
long temp_cnt;
temp_cnt = 0;
// If the "root" equivalence class does not satisfy the privacy criterion, stop here
if (rVerifier.Verify( m_eqvRootClass ) == false)
{
temp_sstream << "Generalization::Anonymize Error: No generalization satisfies the given requirement";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
const vector<Metadata>& r_meta = m_pMicrodata->GetVecMeta();
const vector<UnitValue>& r_micro = m_pMicrodata->GetVecTuple();
const long attr_num = r_meta.size();
const long tuple_num = r_micro.size() / attr_num;
const long qi_num = m_vecQiAttr.size();
// Initialize m_vecGenLevel
m_vecGenLevel.clear();
m_vecGenLevel.insert( m_vecGenLevel.end(), attr_num, -1 );
for (i = 0; i < qi_num; ++i)
{
const vector<long>& r_vec_level = m_vecHrch[m_vecQiAttr[i].m_nAttr].GetVecLevel();
m_vecGenLevel[m_vecQiAttr[i].m_nAttr] = r_vec_level.size();
}
// Starts from the coarsest generalization, i.e., a generalization based on the "root" equivalence class
m_lstEqvClass.clear();
m_lstEqvClass.push_back( m_eqvRootClass );
list<EqvClass> temp_lst_eqvcls;
list<EqvClass> done_lst_eqvcls;
vector<AttrWghtPair> vec_attr_order = m_vecQiAttr;
map<UnitValue, list<EqvClass>::iterator> map_eqvcls;
map<UnitValue, list<EqvClass>::iterator>::iterator map_pos;
pair<long, list<EqvClass>::iterator> temp_pair;
long failure_cnt = 0;
bool gen_failed;
HrchNode temp_node;
// Iteratively refine the generalization
while (failure_cnt < qi_num)
{
// Sort the attributes according to their weights
long cur_attr;
sort( vec_attr_order.begin(), vec_attr_order.end(), CompareByWght() );
// Try to refine the attribute with the highest weight; if fail, try the attribute with the second highest weight, and so on
for (i = 0; i < qi_num; ++i)
{
cur_attr = vec_attr_order[i].m_nAttr;
if (m_vecGenLevel[cur_attr] == 0)
{
++failure_cnt; // If we have reached the leaf level of attribute cur_attr, we are done with it
vec_attr_order[i].m_fWght = 0;
continue;
}
// Try to refine attribute cur_attr
list<EqvClass>::iterator cls_pos;
gen_failed = false;
for (cls_pos = m_lstEqvClass.begin(); cls_pos != m_lstEqvClass.end(); ++cls_pos) // Check each equivalence class
{
// Refine the equivalence class along attribute cur_attr
map_eqvcls.clear();
const EqvClass& r_eqvcls = *cls_pos;
const vector<HrchNode> r_vec_hrch = m_vecHrch[cur_attr].GetVecNode();
long node_begin, node_end;
if (r_eqvcls.m_vecNodePos[cur_attr] < 0)
{
node_begin = node_end = -1;
}
else
{
node_begin = r_vec_hrch[r_eqvcls.m_vecNodePos[cur_attr]].m_nChildLeft;
node_end = r_vec_hrch[r_eqvcls.m_vecNodePos[cur_attr]].m_nChildRight;
}
list<long>::const_iterator tpl_pos;
vector<HrchNode>::const_iterator node_pos;
map<UnitValue, long>::iterator sen_pos;
UnitValue eqvcls_key;
for (tpl_pos = r_eqvcls.m_lstTplId.begin(); tpl_pos != r_eqvcls.m_lstTplId.end(); ++tpl_pos)
{
long tpl_no = *tpl_pos;
if (node_begin == -1)
{
eqvcls_key = r_micro[tpl_no * attr_num + cur_attr];
}
else
{
temp_node.m_uInterval.m_uLeft = temp_node.m_uInterval.m_uRight = r_micro[tpl_no * attr_num + cur_attr];
node_pos = lower_bound( r_vec_hrch.begin() + node_begin, r_vec_hrch.begin() + node_end + 1, temp_node );
eqvcls_key = long( distance( r_vec_hrch.begin(), node_pos ) );
if (eqvcls_key.l == node_end + 1)
{
temp_sstream << "Generalization::Anonymize Error: Value " << cur_attr << " of tuple " << tpl_no << " is not covered in level " << m_vecGenLevel[cur_attr] << " of the hierarchy";
temp_exception.SetMsg( temp_sstream.str() );
throw( temp_exception );
}
}
map_pos = map_eqvcls.find( eqvcls_key );
if (map_pos != map_eqvcls.end())
{
EqvClass& r_target = *((*map_pos).second);
r_target.m_lstTplId.push_back( tpl_no );
map<UnitValue, long>& r_sen_map = r_target.m_mapSenCnt;
sen_pos = r_sen_map.find( r_micro[tpl_no * attr_num + m_nSenAttr] );
if (sen_pos == r_sen_map.end())
{
r_sen_map.insert( pair<UnitValue, long>( r_micro[tpl_no * attr_num + m_nSenAttr], 1 ) );
}
else
{
++(*sen_pos).second;
}
}
else
{
temp_lst_eqvcls.push_front( EqvClass() );
EqvClass& r_target = *temp_lst_eqvcls.begin();
r_target.m_lstTplId.push_back( tpl_no );
r_target.m_mapSenCnt.insert( pair<UnitValue, long>( r_micro[tpl_no * attr_num + m_nSenAttr], 1 ) );
r_target.m_vecNodePos = r_eqvcls.m_vecNodePos;
if (node_begin == -1)
{
r_target.m_vecNodePos[cur_attr] = -1;
}
else
{
r_target.m_vecNodePos[cur_attr] = eqvcls_key.l;
}
map_eqvcls.insert( pair<UnitValue, list<EqvClass>::iterator>( eqvcls_key, temp_lst_eqvcls.begin() ) );
}
}
list<EqvClass>::iterator temp_cls_pos;
for (temp_cls_pos = temp_lst_eqvcls.begin(); temp_cls_pos != temp_lst_eqvcls.end(); ++temp_cls_pos)
{
EqvClass& r_test = *temp_cls_pos;
if (rVerifier.Verify( r_test ) == false)
{
gen_failed = true;
break;
}
}
if (gen_failed == true)
{
temp_lst_eqvcls.clear();
done_lst_eqvcls.clear();
break;
}
done_lst_eqvcls.splice( done_lst_eqvcls.end(), temp_lst_eqvcls );
}
if (gen_failed == true)
{
++failure_cnt;
vec_attr_order[i].m_fWght = 0;
}
else
{
vec_attr_order[i].m_fWght /= 2;
--m_vecGenLevel[cur_attr];
m_lstEqvClass.swap( done_lst_eqvcls );
temp_lst_eqvcls.clear();
done_lst_eqvcls.clear();
break;
}
}
cout << "Current attribute: " << cur_attr << endl;
}
m_vecPtEqv.clear();
m_vecPtEqv.insert( m_vecPtEqv.begin(), m_pMicrodata->GetTupleNum(), NULL );
list<EqvClass>::iterator eqv_pos;
list<long>::const_iterator tpl_pos;
for (eqv_pos = m_lstEqvClass.begin(); eqv_pos != m_lstEqvClass.end(); ++eqv_pos)
{
EqvClass& r_eqv = *eqv_pos;
for (tpl_pos = r_eqv.m_lstTplId.begin(); tpl_pos != r_eqv.m_lstTplId.end(); ++tpl_pos)
{
m_vecPtEqv[*tpl_pos] = &r_eqv;
}
}
m_bGenExists = true;
}
catch( AnonyException e )
{
m_lstEqvClass.clear();
m_vecGenLevel.clear();
m_vecPtEqv.clear();
cout << e.GetMsg() << endl;
m_bGenExists = false;
throw( e );
}
return true;
}
