Add travis sanitizers tests. (#3557)

* Add travis sanitizers tests.

* Add gcc-7 in Travis.
* Add SANITIZER_PATH for CMake.
* Enable sanitizer tests in Travis.

* Fix memory leaks in tests.

* Fix all memory leaks reported by Address Sanitizer.
* tests/cpp/helpers.h/CreateDMatrix now returns raw pointer.

.travis.yml

@@ -28,6 +28,8 @@ env:
     - TASK=cpp_test
     # distributed test
     - TASK=distributed_test
+    # address sanitizer test
+    - TASK=sanitizer_test
 
 matrix:
   exclude:
@@ -43,6 +45,8 @@ matrix:
       env: TASK=cpp_test
     - os: osx
       env: TASK=distributed_test
+    - os: osx
+      env: TASK=sanitizer_test
 
 # dependent apt packages
 addons:
@@ -62,6 +66,8 @@ addons:
       - graphviz
       - gcc-4.8
       - g++-4.8
+      - gcc-7
+      - g++-7
 
 before_install:
   - source dmlc-core/scripts/travis/travis_setup_env.sh

CMakeLists.txt

@@ -14,9 +14,10 @@ option(USE_NCCL "Build using NCCL for multi-GPU. Also requires USE_CUDA")
 option(JVM_BINDINGS "Build JVM bindings" OFF)
 option(GOOGLE_TEST "Build google tests" OFF)
 option(R_LIB "Build shared library for R package" OFF)
-option(USE_SANITIZER "Use santizer flags" OFF)
 set(GPU_COMPUTE_VER "" CACHE STRING
   "Space separated list of compute versions to be built against, e.g. '35 61'")
+option(USE_SANITIZER "Use santizer flags" OFF)
+option(SANITIZER_PATH "Path to sanitizes.")
 set(ENABLED_SANITIZERS "address" "leak" CACHE STRING
   "Semicolon separated list of sanitizer names. E.g 'address;leak'. Supported sanitizers are
 address, leak and thread.")

cmake/modules/FindASan.cmake

@@ -1,8 +1,8 @@
 set(ASan_LIB_NAME ASan)
 
 find_library(ASan_LIBRARY
-  NAMES libasan.so libasan.so.4
+  NAMES libasan.so libasan.so.4 libasan.so.3 libasan.so.2 libasan.so.1 libasan.so.0
-  PATHS /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib)
+  PATHS ${SANITIZER_PATH} /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib ${CMAKE_PREFIX_PATH}/lib)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(ASan DEFAULT_MSG

cmake/modules/FindLSan.cmake

@@ -2,7 +2,7 @@ set(LSan_LIB_NAME lsan)
 
 find_library(LSan_LIBRARY
   NAMES liblsan.so liblsan.so.0 liblsan.so.0.0.0
-  PATHS /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib)
+  PATHS ${SANITIZER_PATH} /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib ${CMAKE_PREFIX_PATH}/lib)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(LSan DEFAULT_MSG

cmake/modules/FindTSan.cmake

@@ -2,7 +2,7 @@ set(TSan_LIB_NAME tsan)
 
 find_library(TSan_LIBRARY
   NAMES libtsan.so libtsan.so.0 libtsan.so.0.0.0
-  PATHS /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib)
+  PATHS ${SANITIZER_PATH} /usr/lib64 /usr/lib /usr/local/lib64 /usr/local/lib ${CMAKE_PREFIX_PATH}/lib)
 
 include(FindPackageHandleStandardArgs)
 find_package_handle_standard_args(TSan DEFAULT_MSG

doc/contribute.rst

@@ -149,6 +149,14 @@ sanitizer is not compatible with the other two sanitizers.
 
     cmake -DUSE_SANITIZER=ON -DENABLED_SANITIZERS="address;leak" /path/to/xgboost
 
+By default, CMake will search regular system paths for sanitizers, you can also
+supply a specified SANITIZER_PATH.
+
+  .. code-block:: bash
+
+    cmake -DUSE_SANITIZER=ON -DENABLED_SANITIZERS="address;leak" \
+    -DSANITIZER_PATH=/path/to/sanitizers /path/to/xgboost
+
 How to use sanitizers with CUDA support
 =======================================
 Runing XGBoost on CUDA with address sanitizer (asan) will raise memory error.

tests/cpp/c_api/test_c_api.cc

@@ -13,14 +13,14 @@ TEST(c_api, XGDMatrixCreateFromMatDT) {
   DMatrixHandle handle;
   XGDMatrixCreateFromDT(data.data(), types.data(), 3, 2, &handle,
                         0);
-  std::shared_ptr<xgboost::DMatrix> dmat =
+  std::shared_ptr<xgboost::DMatrix> *dmat =
-      *static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
+      static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
-  xgboost::MetaInfo &info = dmat->Info();
+  xgboost::MetaInfo &info = (*dmat)->Info();
   ASSERT_EQ(info.num_col_, 2);
   ASSERT_EQ(info.num_row_, 3);
   ASSERT_EQ(info.num_nonzero_, 6);
 
-  auto iter = dmat->RowIterator();
+  auto iter = (*dmat)->RowIterator();
   iter->BeforeFirst();
   while (iter->Next()) {
     auto batch = iter->Value();
@@ -29,6 +29,8 @@ TEST(c_api, XGDMatrixCreateFromMatDT) {
     ASSERT_EQ(batch[2][0].fvalue, 3.0f);
     ASSERT_EQ(batch[2][1].fvalue, 0.0f);
   }
+
+  delete dmat;
 }
 
 TEST(c_api, XGDMatrixCreateFromMat_omp) {
@@ -46,14 +48,14 @@ TEST(c_api, XGDMatrixCreateFromMat_omp) {
                                std::numeric_limits<float>::quiet_NaN(), &handle,
                                0);
 
-    std::shared_ptr<xgboost::DMatrix> dmat =
+    std::shared_ptr<xgboost::DMatrix> *dmat =
-        *static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
+        static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
-    xgboost::MetaInfo &info = dmat->Info();
+    xgboost::MetaInfo &info = (*dmat)->Info();
     ASSERT_EQ(info.num_col_, num_cols);
     ASSERT_EQ(info.num_row_, row);
     ASSERT_EQ(info.num_nonzero_, num_cols * row - num_missing);
 
-    auto iter = dmat->RowIterator();
+    auto iter = (*dmat)->RowIterator();
     iter->BeforeFirst();
     while (iter->Next()) {
       auto batch = iter->Value();
@@ -64,5 +66,6 @@ TEST(c_api, XGDMatrixCreateFromMat_omp) {
         }
       }
     }
+    delete dmat;
   }
 }

tests/cpp/common/test_column_matrix.cc

@@ -7,23 +7,24 @@ namespace common {
 TEST(DenseColumn, Test) {
   auto dmat = CreateDMatrix(100, 10, 0.0);
   GHistIndexMatrix gmat;
-  gmat.Init(dmat.get(), 256);
+  gmat.Init((*dmat).get(), 256);
   ColumnMatrix column_matrix;
   column_matrix.Init(gmat, 0.2);
 
-  for (auto i = 0ull; i < dmat->Info().num_row_; i++) {
+  for (auto i = 0ull; i < (*dmat)->Info().num_row_; i++) {
-    for (auto j = 0ull; j < dmat->Info().num_col_; j++) {
+    for (auto j = 0ull; j < (*dmat)->Info().num_col_; j++) {
         auto col = column_matrix.GetColumn(j);
-        EXPECT_EQ(gmat.index[i * dmat->Info().num_col_ + j],
+        EXPECT_EQ(gmat.index[i * (*dmat)->Info().num_col_ + j],
                   col.GetGlobalBinIdx(i));
     }
   }
+  delete dmat;
 }
 
 TEST(SparseColumn, Test) {
   auto dmat = CreateDMatrix(100, 1, 0.85);
   GHistIndexMatrix gmat;
-  gmat.Init(dmat.get(), 256);
+  gmat.Init((*dmat).get(), 256);
   ColumnMatrix column_matrix;
   column_matrix.Init(gmat, 0.5);
   auto col = column_matrix.GetColumn(0);
@@ -32,12 +33,13 @@ TEST(SparseColumn, Test) {
     EXPECT_EQ(gmat.index[gmat.row_ptr[col.GetRowIdx(i)]],
               col.GetGlobalBinIdx(i));
   }
+  delete dmat;
 }
 
 TEST(DenseColumnWithMissing, Test) {
   auto dmat = CreateDMatrix(100, 1, 0.5);
   GHistIndexMatrix gmat;
-  gmat.Init(dmat.get(), 256);
+  gmat.Init((*dmat).get(), 256);
   ColumnMatrix column_matrix;
   column_matrix.Init(gmat, 0.2);
   auto col = column_matrix.GetColumn(0);
@@ -46,6 +48,7 @@ TEST(DenseColumnWithMissing, Test) {
     EXPECT_EQ(gmat.index[gmat.row_ptr[col.GetRowIdx(i)]],
               col.GetGlobalBinIdx(i));
   }
+  delete dmat;
 }
 }  // namespace common
 }  // namespace xgboost

tests/cpp/common/test_gpu_hist_util.cu

@@ -22,7 +22,7 @@ TEST(gpu_hist_util, TestDeviceSketch) {
   DMatrixHandle dmat_handle;
   XGDMatrixCreateFromMat(test_data.data(), nrows, 1, -1,
                          &dmat_handle);
-  auto dmat = *static_cast<std::shared_ptr<xgboost::DMatrix> *>(dmat_handle);
+  auto dmat = static_cast<std::shared_ptr<xgboost::DMatrix> *>(dmat_handle);
 
   // parameters for finding quantiles
   tree::TrainParam p;
@@ -34,15 +34,15 @@ TEST(gpu_hist_util, TestDeviceSketch) {
 
   // find quantiles on the CPU
   HistCutMatrix hmat_cpu;
-  hmat_cpu.Init(dmat.get(), p.max_bin);
+  hmat_cpu.Init((*dmat).get(), p.max_bin);
 
   // find the cuts on the GPU
-  dmlc::DataIter<SparsePage>* iter = dmat->RowIterator();
+  dmlc::DataIter<SparsePage>* iter = (*dmat)->RowIterator();
   iter->BeforeFirst();
   CHECK(iter->Next());
   const SparsePage& batch = iter->Value();
   HistCutMatrix hmat_gpu;
-  DeviceSketch(batch, dmat->Info(), p, &hmat_gpu);
+  DeviceSketch(batch, (*dmat)->Info(), p, &hmat_gpu);
   CHECK(!iter->Next());
 
   // compare the cuts
@@ -54,6 +54,8 @@ TEST(gpu_hist_util, TestDeviceSketch) {
   for (int i = 0; i < hmat_gpu.cut.size(); ++i) {
     ASSERT_LT(fabs(hmat_cpu.cut[i] - hmat_gpu.cut[i]), eps * nrows);
   }
+
+  delete dmat;
 }
 
 }  // namespace common

tests/cpp/data/test_metainfo.cc

@@ -64,6 +64,8 @@ TEST(MetaInfo, SaveLoadBinary) {
   EXPECT_EQ(inforead.num_row_, info.num_row_);
 
   std::remove(tmp_file.c_str());
+
+  delete fs;
 }
 
 TEST(MetaInfo, LoadQid) {

tests/cpp/data/test_simple_csr_source.cc

@@ -29,4 +29,7 @@ TEST(SimpleCSRSource, SaveLoadBinary) {
   EXPECT_EQ(first_row[2].index, first_row_read[2].index);
   EXPECT_EQ(first_row[2].fvalue, first_row_read[2].fvalue);
   row_iter = nullptr; row_iter_read = nullptr;
+
+  delete dmat;
+  delete dmat_read;
 }

tests/cpp/data/test_simple_dmatrix.cc

@@ -14,6 +14,8 @@ TEST(SimpleDMatrix, MetaInfo) {
   EXPECT_EQ(dmat->Info().num_col_, 5);
   EXPECT_EQ(dmat->Info().num_nonzero_, 6);
   EXPECT_EQ(dmat->Info().labels_.size(), dmat->Info().num_row_);
+
+  delete dmat;
 }
 
 TEST(SimpleDMatrix, RowAccess) {
@@ -35,6 +37,8 @@ TEST(SimpleDMatrix, RowAccess) {
   EXPECT_EQ(first_row[2].index, 2);
   EXPECT_EQ(first_row[2].fvalue, 20);
   row_iter = nullptr;
+
+  delete dmat;
 }
 
 TEST(SimpleDMatrix, ColAccessWithoutBatches) {
@@ -76,4 +80,6 @@ TEST(SimpleDMatrix, ColAccessWithoutBatches) {
   }
   EXPECT_EQ(num_col_batch, 1) << "Expected number of batches to be 1";
   col_iter = nullptr;
+
+  delete dmat;
 }

tests/cpp/data/test_sparse_page_dmatrix.cc

@@ -21,6 +21,8 @@ TEST(SparsePageDMatrix, MetaInfo) {
   // Clean up of external memory files
   std::remove((tmp_file + ".cache").c_str());
   std::remove((tmp_file + ".cache.row.page").c_str());
+
+  delete dmat;
 }
 
 TEST(SparsePageDMatrix, RowAccess) {
@@ -48,6 +50,8 @@ TEST(SparsePageDMatrix, RowAccess) {
   // Clean up of external memory files
   std::remove((tmp_file + ".cache").c_str());
   std::remove((tmp_file + ".cache.row.page").c_str());
+
+  delete dmat;
 }
 
 TEST(SparsePageDMatrix, ColAcess) {
@@ -84,4 +88,6 @@ TEST(SparsePageDMatrix, ColAcess) {
   std::remove((tmp_file + ".cache").c_str());
   std::remove((tmp_file + ".cache.col.page").c_str());
   std::remove((tmp_file + ".cache.row.page").c_str());
+
+  delete dmat;
 }

tests/cpp/helpers.cc

@@ -107,7 +107,7 @@ xgboost::bst_float GetMetricEval(xgboost::Metric * metric,
   return metric->Eval(preds, info, false);
 }
 
-std::shared_ptr<xgboost::DMatrix> CreateDMatrix(int rows, int columns,
+std::shared_ptr<xgboost::DMatrix>* CreateDMatrix(int rows, int columns,
                                                  float sparsity, int seed) {
   const float missing_value = -1;
   std::vector<float> test_data(rows * columns);
@@ -124,5 +124,5 @@ std::shared_ptr<xgboost::DMatrix> CreateDMatrix(int rows, int columns,
   DMatrixHandle handle;
   XGDMatrixCreateFromMat(test_data.data(), rows, columns, missing_value,
                          &handle);
-  return *static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
+  return static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
 }

tests/cpp/helpers.h

@@ -59,6 +59,6 @@ xgboost::bst_float GetMetricEval(
  * \return  The new d matrix.
  */
 
-std::shared_ptr<xgboost::DMatrix> CreateDMatrix(int rows, int columns,
+std::shared_ptr<xgboost::DMatrix> *CreateDMatrix(int rows, int columns,
                                                  float sparsity, int seed = 0);
 #endif

tests/cpp/linear/test_linear.cc

@@ -8,37 +8,41 @@ typedef std::pair<std::string, std::string> arg;
 TEST(Linear, shotgun) {
   typedef std::pair<std::string, std::string> arg;
   auto mat = CreateDMatrix(10, 10, 0);
-  std::vector<bool> enabled(mat->Info().num_col_, true);
+  std::vector<bool> enabled((*mat)->Info().num_col_, true);
-  mat->InitColAccess(1 << 16, false);
+  (*mat)->InitColAccess(1 << 16, false);
   auto updater = std::unique_ptr<xgboost::LinearUpdater>(
       xgboost::LinearUpdater::Create("shotgun"));
   updater->Init({{"eta", "1."}});
   xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
-      mat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
+      (*mat)->Info().num_row_, xgboost::GradientPair(-5, 1.0));
   xgboost::gbm::GBLinearModel model;
-  model.param.num_feature = mat->Info().num_col_;
+  model.param.num_feature = (*mat)->Info().num_col_;
   model.param.num_output_group = 1;
   model.LazyInitModel();
-  updater->Update(&gpair, mat.get(), &model, gpair.Size());
+  updater->Update(&gpair, (*mat).get(), &model, gpair.Size());
 
   ASSERT_EQ(model.bias()[0], 5.0f);
+
+  delete mat;
 }
 
 TEST(Linear, coordinate) {
   typedef std::pair<std::string, std::string> arg;
   auto mat = CreateDMatrix(10, 10, 0);
-  std::vector<bool> enabled(mat->Info().num_col_, true);
+  std::vector<bool> enabled((*mat)->Info().num_col_, true);
-  mat->InitColAccess(1 << 16, false);
+  (*mat)->InitColAccess(1 << 16, false);
   auto updater = std::unique_ptr<xgboost::LinearUpdater>(
       xgboost::LinearUpdater::Create("coord_descent"));
   updater->Init({{"eta", "1."}});
   xgboost::HostDeviceVector<xgboost::GradientPair> gpair(
-      mat->Info().num_row_, xgboost::GradientPair(-5, 1.0));
+      (*mat)->Info().num_row_, xgboost::GradientPair(-5, 1.0));
   xgboost::gbm::GBLinearModel model;
-  model.param.num_feature = mat->Info().num_col_;
+  model.param.num_feature = (*mat)->Info().num_col_;
   model.param.num_output_group = 1;
   model.LazyInitModel();
-  updater->Update(&gpair, mat.get(), &model, gpair.Size());
+  updater->Update(&gpair, (*mat).get(), &model, gpair.Size());
 
   ASSERT_EQ(model.bias()[0], 5.0f);
+
+  delete mat;
 }

tests/cpp/metric/test_elementwise_metric.cc

@@ -11,6 +11,7 @@ TEST(Metric, RMSE) {
                             {0.1f, 0.9f, 0.1f, 0.9f},
                             {  0,   0,   1,   1}),
               0.6403f, 0.001f);
+  delete metric;
 }
 
 TEST(Metric, MAE) {
@@ -21,6 +22,7 @@ TEST(Metric, MAE) {
                             {0.1f, 0.9f, 0.1f, 0.9f},
                             {  0,   0,   1,   1}),
               0.5f, 0.001f);
+  delete metric;
 }
 
 TEST(Metric, LogLoss) {
@@ -31,6 +33,7 @@ TEST(Metric, LogLoss) {
                             {0.1f, 0.9f, 0.1f, 0.9f},
                             {  0,   0,   1,   1}),
               1.2039f, 0.001f);
+  delete metric;
 }
 
 TEST(Metric, Error) {
@@ -56,6 +59,7 @@ TEST(Metric, Error) {
                             {0.1f, 0.2f, 0.1f, 0.2f},
                             {  0,   0,   1,   1}),
               0.5f, 0.001f);
+  delete metric;
 }
 
 TEST(Metric, PoissionNegLogLik) {
@@ -66,4 +70,5 @@ TEST(Metric, PoissionNegLogLik) {
                             {0.1f, 0.2f, 0.1f, 0.2f},
                             {  0,   0,   1,   1}),
               1.1280f, 0.001f);
+  delete metric;
 }

tests/cpp/metric/test_metric.cc

@@ -4,8 +4,11 @@
 #include "../helpers.h"
 
 TEST(Metric, UnknownMetric) {
-  EXPECT_ANY_THROW(xgboost::Metric::Create("unknown_name"));
+  xgboost::Metric * metric;
-  EXPECT_NO_THROW(xgboost::Metric::Create("rmse"));
+  EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name"));
-  EXPECT_ANY_THROW(xgboost::Metric::Create("unknown_name@1"));
+  EXPECT_NO_THROW(metric = xgboost::Metric::Create("rmse"));
-  EXPECT_NO_THROW(xgboost::Metric::Create("error@0.5f"));
+  delete metric;
+  EXPECT_ANY_THROW(metric = xgboost::Metric::Create("unknown_name@1"));
+  EXPECT_NO_THROW(metric = xgboost::Metric::Create("error@0.5f"));
+  delete metric;
 }

tests/cpp/metric/test_multiclass_metric.cc

@@ -13,6 +13,8 @@ TEST(Metric, MultiClassError) {
                             {0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f},
                             {0, 1, 2}),
               0.666f, 0.001f);
+
+  delete metric;
 }
 
 TEST(Metric, MultiClassLogLoss) {
@@ -25,4 +27,6 @@ TEST(Metric, MultiClassLogLoss) {
                             {0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f, 0.1f},
                             {0, 1, 2}),
               2.302f, 0.001f);
+
+  delete metric;
 }

tests/cpp/metric/test_rank_metric.cc

@@ -17,6 +17,8 @@ TEST(Metric, AMS) {
   metric = xgboost::Metric::Create("ams@0");
   ASSERT_STREQ(metric->Name(), "ams@0");
   EXPECT_NEAR(GetMetricEval(metric, {0, 1}, {0, 1}), 0.311f, 0.001f);
+
+  delete metric;
 }
 
 TEST(Metric, AUC) {
@@ -29,6 +31,8 @@ TEST(Metric, AUC) {
               0.5f, 0.001f);
   EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
   EXPECT_ANY_THROW(GetMetricEval(metric, {0, 0}, {0, 0}));
+
+  delete metric;
 }
 
 TEST(Metric, AUCPR) {
@@ -50,6 +54,8 @@ TEST(Metric, AUCPR) {
               0.2769199f, 0.001f);
   EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
   EXPECT_ANY_THROW(GetMetricEval(metric, {0, 0}, {0, 0}));
+
+  delete metric;
 }
 
 TEST(Metric, Precision) {
@@ -74,6 +80,8 @@ TEST(Metric, Precision) {
               0.5f, 0.001f);
 
   EXPECT_ANY_THROW(GetMetricEval(metric, {0, 1}, {}));
+
+  delete metric;
 }
 
 TEST(Metric, NDCG) {
@@ -114,6 +122,8 @@ TEST(Metric, NDCG) {
                             {0.1f, 0.9f, 0.1f, 0.9f},
                             {  0,   0,   1,   1}),
               0.3868f, 0.001f);
+
+  delete metric;
 }
 
 TEST(Metric, MAP) {
@@ -139,4 +149,5 @@ TEST(Metric, MAP) {
                             {0.1f, 0.9f, 0.1f, 0.9f},
                             {  0,   0,   1,   1}),
               0.25f, 0.001f);
+  delete metric;
 }

tests/cpp/objective/test_hinge.cc

@@ -17,4 +17,6 @@ TEST(Objective, HingeObj) {
                    {  eps,  1.0f, 1.0f, 1.0f,  1.0f,  1.0f,  1.0f, eps });
 
   ASSERT_NO_THROW(obj->DefaultEvalMetric());
+
+  delete obj;
 }

tests/cpp/objective/test_objective.cc

@@ -4,6 +4,8 @@
 #include "../helpers.h"
 
 TEST(Objective, UnknownFunction) {
-  EXPECT_ANY_THROW(xgboost::ObjFunction::Create("unknown_name"));
+  xgboost::ObjFunction* obj;
-  EXPECT_NO_THROW(xgboost::ObjFunction::Create("reg:linear"));
+  EXPECT_ANY_THROW(obj = xgboost::ObjFunction::Create("unknown_name"));
+  EXPECT_NO_THROW(obj = xgboost::ObjFunction::Create("reg:linear"));
+  delete obj;
 }

tests/cpp/objective/test_ranking_obj.cc

@@ -25,4 +25,6 @@ TEST(Objective, PairwiseRankingGPair) {
                    {0.9975f, 0.9975f, 0.9975f, 0.9975f});
 
   ASSERT_NO_THROW(obj->DefaultEvalMetric());
+
+  delete obj;
 }

tests/cpp/objective/test_regression_obj.cc

@@ -15,6 +15,8 @@ TEST(Objective, LinearRegressionGPair) {
                    {1,   1,   1,   1,    1,    1,    1, 1});
 
   ASSERT_NO_THROW(obj->DefaultEvalMetric());
+
+  delete obj;
 }
 
 TEST(Objective, LogisticRegressionGPair) {
@@ -27,6 +29,8 @@ TEST(Objective, LogisticRegressionGPair) {
                    {   1,    1,    1,    1,    1,     1,     1,     1},
                    { 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
                    {0.25f, 0.24f, 0.20f, 0.19f, 0.25f,  0.24f,  0.20f,  0.19f});
+
+  delete obj;
 }
 
 TEST(Objective, LogisticRegressionBasic) {
@@ -53,6 +57,8 @@ TEST(Objective, LogisticRegressionBasic) {
   for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
     EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
   }
+
+  delete obj;
 }
 
 TEST(Objective, LogisticRawGPair) {
@@ -65,6 +71,8 @@ TEST(Objective, LogisticRawGPair) {
                    {   1,    1,    1,    1,    1,     1,     1,     1},
                    { 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
                    {0.25f, 0.24f, 0.20f, 0.19f, 0.25f,  0.24f,  0.20f,  0.19f});
+
+  delete obj;
 }
 
 TEST(Objective, PoissonRegressionGPair) {
@@ -78,6 +86,8 @@ TEST(Objective, PoissonRegressionGPair) {
                    {   1,    1,    1,    1,    1,    1,    1,    1},
                    {   1, 1.10f, 2.45f, 2.71f,    0, 0.10f, 1.45f, 1.71f},
                    {1.10f, 1.22f, 2.71f, 3.00f, 1.10f, 1.22f, 2.71f, 3.00f});
+
+  delete obj;
 }
 
 TEST(Objective, PoissonRegressionBasic) {
@@ -102,6 +112,8 @@ TEST(Objective, PoissonRegressionBasic) {
   for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
     EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
   }
+
+  delete obj;
 }
 
 TEST(Objective, GammaRegressionGPair) {
@@ -114,6 +126,8 @@ TEST(Objective, GammaRegressionGPair) {
                    {1,   1,   1, 1, 1,    1,    1,    1},
                    {1,   1,   1, 1, 0, 0.09f, 0.59f, 0.63f},
                    {0,   0,   0, 0, 1, 0.90f, 0.40f, 0.36f});
+
+  delete obj;
 }
 
 TEST(Objective, GammaRegressionBasic) {
@@ -138,6 +152,8 @@ TEST(Objective, GammaRegressionBasic) {
   for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
     EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
   }
+
+  delete obj;
 }
 
 TEST(Objective, TweedieRegressionGPair) {
@@ -151,6 +167,8 @@ TEST(Objective, TweedieRegressionGPair) {
                    {   1,    1,    1,    1, 1,    1,    1,    1},
                    {   1, 1.09f, 2.24f, 2.45f, 0, 0.10f, 1.33f, 1.55f},
                    {0.89f, 0.98f, 2.02f, 2.21f, 1, 1.08f, 2.11f, 2.30f});
+
+  delete obj;
 }
 
 TEST(Objective, TweedieRegressionBasic) {
@@ -175,6 +193,8 @@ TEST(Objective, TweedieRegressionBasic) {
   for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
     EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
   }
+
+  delete obj;
 }
 
 TEST(Objective, CoxRegressionGPair) {
@@ -187,4 +207,6 @@ TEST(Objective, CoxRegressionGPair) {
                    { 1,    1,    1,       1,       1,       1,      1,       1},
                    { 0,    0,    0, -0.799f, -0.788f, -0.590f, 0.910f,  1.006f},
                    { 0,    0,    0,  0.160f,  0.186f,  0.348f, 0.610f,  0.639f});
+
+  delete obj;
 }

tests/cpp/objective/test_regression_obj_gpu.cu

@@ -17,6 +17,8 @@ TEST(Objective, GPULinearRegressionGPair) {
                    {1,   1,   1,   1,    1,    1,    1, 1});
 
   ASSERT_NO_THROW(obj->DefaultEvalMetric());
+
+  delete obj;
 }
 
 TEST(Objective, GPULogisticRegressionGPair) {
@@ -29,6 +31,8 @@ TEST(Objective, GPULogisticRegressionGPair) {
                    {   1,    1,    1,    1,    1,     1,     1,     1},
                    { 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
                    {0.25f, 0.24f, 0.20f, 0.19f, 0.25f,  0.24f,  0.20f,  0.19f});
+
+  delete obj;
 }
 
 TEST(Objective, GPULogisticRegressionBasic) {
@@ -55,6 +59,8 @@ TEST(Objective, GPULogisticRegressionBasic) {
   for (int i = 0; i < static_cast<int>(io_preds.Size()); ++i) {
     EXPECT_NEAR(preds[i], out_preds[i], 0.01f);
   }
+
+  delete obj;
 }
 
 TEST(Objective, GPULogisticRawGPair) {
@@ -67,4 +73,6 @@ TEST(Objective, GPULogisticRawGPair) {
                    {   1,    1,    1,    1,    1,     1,     1,     1},
                    { 0.5f, 0.52f, 0.71f, 0.73f, -0.5f, -0.47f, -0.28f, -0.26f},
                    {0.25f, 0.24f, 0.20f, 0.19f, 0.25f,  0.24f,  0.20f,  0.19f});
+
+  delete obj;
 }

tests/cpp/predictor/test_cpu_predictor.cc

@@ -25,14 +25,14 @@ TEST(cpu_predictor, Test) {
 
   // Test predict batch
   HostDeviceVector<float> out_predictions;
-  cpu_predictor->PredictBatch(dmat.get(), &out_predictions, model, 0);
+  cpu_predictor->PredictBatch((*dmat).get(), &out_predictions, model, 0);
   std::vector<float>& out_predictions_h = out_predictions.HostVector();
   for (int i = 0; i < out_predictions.Size(); i++) {
     ASSERT_EQ(out_predictions_h[i], 1.5);
   }
 
   // Test predict instance
-  auto batch = dmat->RowIterator()->Value();
+  auto batch = (*dmat)->RowIterator()->Value();
   for (int i = 0; i < batch.Size(); i++) {
     std::vector<float> instance_out_predictions;
     cpu_predictor->PredictInstance(batch[i], &instance_out_predictions, model);
@@ -41,22 +41,24 @@ TEST(cpu_predictor, Test) {
 
   // Test predict leaf
   std::vector<float> leaf_out_predictions;
-  cpu_predictor->PredictLeaf(dmat.get(), &leaf_out_predictions, model);
+  cpu_predictor->PredictLeaf((*dmat).get(), &leaf_out_predictions, model);
   for (int i = 0; i < leaf_out_predictions.size(); i++) {
     ASSERT_EQ(leaf_out_predictions[i], 0);
   }
 
   // Test predict contribution
   std::vector<float> out_contribution;
-  cpu_predictor->PredictContribution(dmat.get(), &out_contribution, model);
+  cpu_predictor->PredictContribution((*dmat).get(), &out_contribution, model);
   for (int i = 0; i < out_contribution.size(); i++) {
     ASSERT_EQ(out_contribution[i], 1.5);
   }
 
   // Test predict contribution (approximate method)
-  cpu_predictor->PredictContribution(dmat.get(), &out_contribution, model, true);
+  cpu_predictor->PredictContribution((*dmat).get(), &out_contribution, model, true);
   for (int i = 0; i < out_contribution.size(); i++) {
     ASSERT_EQ(out_contribution[i], 1.5);
   }
+
+  delete dmat;
 }
 }  // namespace xgboost

tests/cpp/predictor/test_gpu_predictor.cu

@@ -35,8 +35,8 @@ TEST(gpu_predictor, Test) {
   // Test predict batch
   HostDeviceVector<float> gpu_out_predictions;
   HostDeviceVector<float> cpu_out_predictions;
-  gpu_predictor->PredictBatch(dmat.get(), &gpu_out_predictions, model, 0);
+  gpu_predictor->PredictBatch((*dmat).get(), &gpu_out_predictions, model, 0);
-  cpu_predictor->PredictBatch(dmat.get(), &cpu_out_predictions, model, 0);
+  cpu_predictor->PredictBatch((*dmat).get(), &cpu_out_predictions, model, 0);
   std::vector<float>& gpu_out_predictions_h = gpu_out_predictions.HostVector();
   std::vector<float>& cpu_out_predictions_h = cpu_out_predictions.HostVector();
   float abs_tolerance = 0.001;
@@ -45,7 +45,7 @@ TEST(gpu_predictor, Test) {
               abs_tolerance);
   }
   // Test predict instance
-  auto batch = dmat->RowIterator()->Value();
+  auto batch = (*dmat)->RowIterator()->Value();
   for (int i = 0; i < batch.Size(); i++) {
     std::vector<float> gpu_instance_out_predictions;
     std::vector<float> cpu_instance_out_predictions;
@@ -59,8 +59,8 @@ TEST(gpu_predictor, Test) {
   // Test predict leaf
   std::vector<float> gpu_leaf_out_predictions;
   std::vector<float> cpu_leaf_out_predictions;
-  cpu_predictor->PredictLeaf(dmat.get(), &cpu_leaf_out_predictions, model);
+  cpu_predictor->PredictLeaf((*dmat).get(), &cpu_leaf_out_predictions, model);
-  gpu_predictor->PredictLeaf(dmat.get(), &gpu_leaf_out_predictions, model);
+  gpu_predictor->PredictLeaf((*dmat).get(), &gpu_leaf_out_predictions, model);
   for (int i = 0; i < gpu_leaf_out_predictions.size(); i++) {
     ASSERT_EQ(gpu_leaf_out_predictions[i], cpu_leaf_out_predictions[i]);
   }
@@ -68,11 +68,13 @@ TEST(gpu_predictor, Test) {
   // Test predict contribution
   std::vector<float> gpu_out_contribution;
   std::vector<float> cpu_out_contribution;
-  cpu_predictor->PredictContribution(dmat.get(), &cpu_out_contribution, model);
+  cpu_predictor->PredictContribution((*dmat).get(), &cpu_out_contribution, model);
-  gpu_predictor->PredictContribution(dmat.get(), &gpu_out_contribution, model);
+  gpu_predictor->PredictContribution((*dmat).get(), &gpu_out_contribution, model);
   for (int i = 0; i < gpu_out_contribution.size(); i++) {
     ASSERT_EQ(gpu_out_contribution[i], cpu_out_contribution[i]);
   }
+
+  delete dmat;
 }
 }  // namespace predictor
 }  // namespace xgboost

tests/cpp/test_learner.cc

@@ -1,5 +1,6 @@
 // Copyright by Contributors
 #include <gtest/gtest.h>
+#include <vector>
 #include "helpers.h"
 #include "xgboost/learner.h"
 
@@ -7,8 +8,11 @@ namespace xgboost {
 TEST(learner, Test) {
   typedef std::pair<std::string, std::string> arg;
   auto args = {arg("tree_method", "exact")};
-  auto mat = {CreateDMatrix(10, 10, 0)};
+  auto mat_ptr = CreateDMatrix(10, 10, 0);
+  std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {*mat_ptr};
   auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
   learner->Configure(args);
+
+  delete mat_ptr;
 }
 }  // namespace xgboost

tests/cpp/tree/test_gpu_hist.cu

@@ -19,11 +19,11 @@ TEST(gpu_hist_experimental, TestSparseShard) {
   int max_bins = 4;
   auto dmat = CreateDMatrix(rows, columns, 0.9f);
   common::GHistIndexMatrix gmat;
-  gmat.Init(dmat.get(),max_bins);
+  gmat.Init((*dmat).get(),max_bins);
   TrainParam p;
   p.max_depth = 6;
 
-  dmlc::DataIter<SparsePage>* iter = dmat->RowIterator();
+  dmlc::DataIter<SparsePage>* iter = (*dmat)->RowIterator();
   iter->BeforeFirst();
   CHECK(iter->Next());
   const SparsePage& batch = iter->Value();
@@ -50,6 +50,8 @@ TEST(gpu_hist_experimental, TestSparseShard) {
       ASSERT_EQ(gidx[i * shard.row_stride + row_offset], shard.null_gidx_value);
     }
   }
+
+  delete dmat;
 }
 
 TEST(gpu_hist_experimental, TestDenseShard) {
@@ -58,11 +60,11 @@ TEST(gpu_hist_experimental, TestDenseShard) {
   int max_bins = 4;
   auto dmat = CreateDMatrix(rows, columns, 0);
   common::GHistIndexMatrix gmat;
-  gmat.Init(dmat.get(),max_bins);
+  gmat.Init((*dmat).get(),max_bins);
   TrainParam p;
   p.max_depth = 6;
 
-  dmlc::DataIter<SparsePage>* iter = dmat->RowIterator();
+  dmlc::DataIter<SparsePage>* iter = (*dmat)->RowIterator();
   iter->BeforeFirst();
   CHECK(iter->Next());
   const SparsePage& batch = iter->Value();
@@ -82,6 +84,8 @@ TEST(gpu_hist_experimental, TestDenseShard) {
   for (int i = 0; i < gmat.index.size(); i++) {
     ASSERT_EQ(gidx[i], gmat.index[i]);
   }
+
+  delete dmat;
 }
 
 }  // namespace tree

tests/travis/run_test.sh

@@ -149,9 +149,39 @@ if [ ${TASK} == "cpp_test" ]; then
     make cover
 fi
 
+
 if [ ${TASK} == "distributed_test" ]; then
     set -e
     make all || exit -1
     cd tests/distributed
     ./runtests.sh
 fi
+
+if [ ${TASK} == "sanitizer_test" ]; then
+    set -e
+    # Build gtest via cmake
+    wget -nc https://github.com/google/googletest/archive/release-1.7.0.zip
+    unzip -n release-1.7.0.zip
+    mv googletest-release-1.7.0 gtest && cd gtest
+    CC=gcc-7 CXX=g++-7 cmake -DCMAKE_CXX_FLAGS="-fuse-ld=gold" \
+      -DCMAKE_C_FLAGS="-fuse-ld=gold"
+    make
+    mkdir lib && mv libgtest.a lib
+    cd ..
+    rm -rf release-1.7.0.zip
+
+    mkdir build && cd build
+    CC=gcc-7 CXX=g++-7 cmake .. -DGOOGLE_TEST=ON -DGTEST_ROOT=$PWD/../gtest/ \
+      -DUSE_SANITIZER=ON -DENABLED_SANITIZERS="address" \
+      -DCMAKE_BUILD_TYPE=Debug \
+      -DSANITIZER_PATH=/usr/lib/x86_64-linux-gnu/ \
+      -DCMAKE_CXX_FLAGS="-fuse-ld=gold" \
+      -DCMAKE_C_FLAGS="-fuse-ld=gold"
+    make
+    cd ..
+
+    export ASAN_SYMBOLIZER_PATH=$(which llvm-symbolizer)
+    ASAN_OPTIONS=symbolize=1 ./testxgboost
+    rm -rf build
+    exit 0
+fi