diff --git a/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_hcom_tailing_optimizer.cpp b/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_hcom_tailing_optimizer.cpp
index afee34778e6d2666c62cc4fbad8ad09e02f83254..50634d80207431e08c239c7818d9585df2954b93 100644
--- a/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_hcom_tailing_optimizer.cpp
+++ b/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_hcom_tailing_optimizer.cpp
@@ -56,7 +56,7 @@ tensorflow::Status TailingOptimizeInner(tensorflow::FunctionLibraryDefinition *l
         }
       }
     }
-    if (node->type_string() == kNpuAllocFloatStatusOp && node->attrs().Find(kNpuLossScaleAttr) != nullptr) {
+    if ((node->type_string() == kNpuAllocFloatStatusOp) && (node->attrs().Find(kNpuLossScaleAttr) != nullptr)) {
       std::unordered_set<const tensorflow::Edge *> edges_to_remove;
       tensorflow::Node *last_allreduce = nullptr;
       for (auto in_edge : node->in_edges()) {
diff --git a/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_weight_update_grouping_optimizer.cpp b/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_weight_update_grouping_optimizer.cpp
index d36a3ca41bc63785867b010d1b63ecb13b544e16..d906256666a6820affc7807a6c9600849daff988 100644
--- a/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_weight_update_grouping_optimizer.cpp
+++ b/tf_adapter_2.x/npu_device/core/optimizers/meta/npu_weight_update_grouping_optimizer.cpp
@@ -57,7 +57,7 @@ tensorflow::Status WeightUpdateGroupingOptimizeInner(tensorflow::FunctionLibrary
       }
     }
 
-    if (node->type_string() == kHcomBroadcast && node->attrs().Find(kWeightUpdateGroupingAttr) != nullptr) {
+    if ((node->type_string() == kHcomBroadcast) && (node->attrs().Find(kWeightUpdateGroupingAttr)) != nullptr) {
       std::unordered_set<const tensorflow::Edge *> edges_to_remove;
       tensorflow::Node *read_var_node = nullptr;
       for (auto in_edge : node->in_edges()) {
@@ -114,7 +114,7 @@ tensorflow::Status WeightUpdateGroupingOptimizeInner(tensorflow::FunctionLibrary
       (void)graph->AddEdge(var_node, 0, new_read_var_node, 0);
       (void)graph->AddEdge(new_read_var_node, 0, node, 0);
       for (auto var_edge : var_node->out_edges()) {
-        if (var_edge->dst() != new_read_var_node && var_edge->dst() != assign_node) {
+        if ((var_edge->dst() != new_read_var_node) && (var_edge->dst() != assign_node)) {
           (void)graph->AddControlEdge(assign_node, var_edge->dst());
         }
       }
diff --git a/tf_adapter_2.x/npu_device/core/optimizers/runtime/node_placer.cpp b/tf_adapter_2.x/npu_device/core/optimizers/runtime/node_placer.cpp
index 92d8c163bd83a959e3b0f7f83b44bf0e78b83dfd..5549135b7ed3aeb4ae474ad3a1cc59a771473909 100644
--- a/tf_adapter_2.x/npu_device/core/optimizers/runtime/node_placer.cpp
+++ b/tf_adapter_2.x/npu_device/core/optimizers/runtime/node_placer.cpp
@@ -316,7 +316,7 @@ tensorflow::Status NodePlacer::PlaceCpuNodeSubgraphs(size_t depth) const {
 bool NodePlacer::IsClusterMustPlaceOnNpu(const Cluster &cluster) {
   for (auto node : cluster.nodes) {
     auto iter = node_placement_.find(node);
-    if (iter != node_placement_.end() && iter->second == Placement::NPU) {
+    if ((iter != node_placement_.end()) && (iter->second == Placement::NPU)) {
       DLOG() << cluster.name << " must place on npu as has determined npu node " << node->name();
       return true;
     }
@@ -405,7 +405,7 @@ void NodePlacer::Concrete(tensorflow::Node *src, tensorflow::Node *dst) {
   DLOG() << "Concrete node " << src->name() << " with " << dst->name() << " to cluster " << target->name;
 
   auto iter = concrete_clusters_.find(src);
-  if (iter != concrete_clusters_.end() && iter->second == target) {
+  if ((iter != concrete_clusters_.end()) && (iter->second == target)) {
     DLOG() << "Node " << src->name() << " has already concrete with " << dst->name() << " in cluster " << target->name;
     return;
   }
@@ -468,7 +468,7 @@ tensorflow::Status NodePlacer::BuildConcreteCluster() {
     std::queue<std::shared_ptr<Cluster>> q;
     for (auto &node : cluster->nodes) {
       auto iter = concrete_clusters_.find(node);
-      if (iter != concrete_clusters_.end() && iter->second != cluster) {
+      if ((iter != concrete_clusters_.end()) && (iter->second != cluster)) {
         q.push(iter->second);
       }
     }
diff --git a/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_build_npu_op_optimizer.cpp b/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_build_npu_op_optimizer.cpp
index 5abc96bfe1936fcf04cc732018042f6bf2a90c87..dd26e7985310e913d92b2df735a89f7c70380d15 100644
--- a/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_build_npu_op_optimizer.cpp
+++ b/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_build_npu_op_optimizer.cpp
@@ -113,7 +113,7 @@ tensorflow::Status TryToBuildShapeForDynDims(const std::map<std::string, std::st
     (options.find(ge::DYNAMIC_NODE_TYPE) == options.end()) ? "" : options.at(ge::DYNAMIC_NODE_TYPE);
   std::string dynamic_dims = (options.find(ge::kDynamicDims) == options.end()) ? "" : options.at(ge::kDynamicDims);
   bool need_dyn_proc = (!input_shapes.empty()) && (!dynamic_node_type.empty()) && (!dynamic_dims.empty());
-  if (!need_dyn_proc || dynamic_node_type == kDynamicNodeTypeData) {
+  if ((!need_dyn_proc) || (dynamic_node_type == kDynamicNodeTypeData)) {
     DLOG() << "Skip dynamic dims. Option configuration is complete:" << (need_dyn_proc ? "true" : "false")
            << ", dynamic_node_type(0 for GetNext, 1 for Data):" << dynamic_node_type;
     return tensorflow::Status::OK();
@@ -159,7 +159,7 @@ tensorflow::Status BuildNpuOpOptimize(TFE_Context *context, NpuMutableConcreteGr
   }
   if (!ss.str().empty()) {
     tensorflow::Node *key;
-    if (IsGraphNeedLoop(*(graph->MutableGraph()), key) || key != nullptr) {
+    if (IsGraphNeedLoop(*(graph->MutableGraph()), key) || (key != nullptr)) {
       graph->SetLoopType(NpuConcreteGraph::LoopType::BUILTIN_LOOP);
     }
     graph->SetExecutionType(NpuConcreteGraph::ExecutionType::MIX);
diff --git a/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_trans_resource_input_to_node_optimizer.cpp b/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_trans_resource_input_to_node_optimizer.cpp
index 2bd9a99c4d7cde50b25f9dbd7934c45244a1419a..6cb0a2bc50730936039a863ad82f596033690ea1 100644
--- a/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_trans_resource_input_to_node_optimizer.cpp
+++ b/tf_adapter_2.x/npu_device/core/optimizers/runtime/npu_trans_resource_input_to_node_optimizer.cpp
@@ -180,7 +180,8 @@ tensorflow::Status TransHasSubgraphNode(TFE_Context *context, tensorflow::Graph
     functions.emplace_back(const_cast<tensorflow::AttrValue*>(node->attrs().Find("then_branch"))->mutable_func());
     functions.emplace_back(const_cast<tensorflow::AttrValue*>(node->attrs().Find("else_branch"))->mutable_func());
   } else if (node->IsCaseNode()) {
-    for (auto &f : *const_cast<tensorflow::AttrValue*>(node->attrs().Find("branches"))->mutable_list()->mutable_func()) {
+    for (auto &f :
+         *const_cast<tensorflow::AttrValue *>(node->attrs().Find("branches"))->mutable_list()->mutable_func()) {
       functions.emplace_back(&f);
     }
   } else {