diff --git a/examples/benchmark_performance/coordinated_lr/test_lr.py b/examples/benchmark_performance/coordinated_lr/test_lr.py
index a5652d0fbc..d92d2787ae 100644
--- a/examples/benchmark_performance/coordinated_lr/test_lr.py
+++ b/examples/benchmark_performance/coordinated_lr/test_lr.py
@@ -74,7 +74,7 @@ def main(config="../../config.yaml", param="./lr_config.yaml", namespace=""):
                          input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["auc", "binary_precision", "binary_accuracy", "binary_recall"],
                               input_data=lr_0.outputs["train_output_data"])
     pipeline.add_task(reader_0)
diff --git a/examples/benchmark_performance/sshe_lr/test_lr.py b/examples/benchmark_performance/sshe_lr/test_lr.py
index 22bdc8c20f..5634db65f4 100644
--- a/examples/benchmark_performance/sshe_lr/test_lr.py
+++ b/examples/benchmark_performance/sshe_lr/test_lr.py
@@ -73,7 +73,7 @@ def main(config="../../config.yaml", param="./lr_config.yaml", namespace=""):
                   input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["auc", "binary_precision", "binary_accuracy", "binary_recall"],
                               input_data=lr_0.outputs["train_output_data"])
     pipeline.add_task(reader_0)
diff --git a/examples/benchmark_quality/linr/fate-linr.py b/examples/benchmark_quality/linr/fate-linr.py
index 397a2f6b33..b314f1a4ba 100644
--- a/examples/benchmark_quality/linr/fate-linr.py
+++ b/examples/benchmark_quality/linr/fate-linr.py
@@ -69,7 +69,7 @@ def main(config="../../config.yaml", param="./linr_config.yaml", namespace=""):
                              input_model=linr_0.outputs["output_model"])"""
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["r2_score",
                                        "mse",
                                        "rmse"],
diff --git a/examples/benchmark_quality/linr/fate-sshe-linr.py b/examples/benchmark_quality/linr/fate-sshe-linr.py
index fab0c78e15..f77bd29872 100644
--- a/examples/benchmark_quality/linr/fate-sshe-linr.py
+++ b/examples/benchmark_quality/linr/fate-sshe-linr.py
@@ -69,7 +69,7 @@ def main(config="../../config.yaml", param="./linr_config.yaml", namespace=""):
                              input_model=linr_0.outputs["output_model"])"""
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["r2_score",
                                        "mse",
                                        "rmse"],
diff --git a/examples/benchmark_quality/lr/pipeline-lr-binary.py b/examples/benchmark_quality/lr/pipeline-lr-binary.py
index 2d8e74f870..e78ddea7fe 100644
--- a/examples/benchmark_quality/lr/pipeline-lr-binary.py
+++ b/examples/benchmark_quality/lr/pipeline-lr-binary.py
@@ -71,7 +71,7 @@ def main(config="../../config.yaml", param="./breast_config.yaml", namespace="")
                          input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["auc", "binary_precision", "binary_accuracy", "binary_recall"],
                               input_data=lr_0.outputs["train_output_data"])
     pipeline.add_task(reader_0)
diff --git a/examples/benchmark_quality/lr/pipeline-lr-multi.py b/examples/benchmark_quality/lr/pipeline-lr-multi.py
index 8e26174e5e..c0914f1a69 100644
--- a/examples/benchmark_quality/lr/pipeline-lr-multi.py
+++ b/examples/benchmark_quality/lr/pipeline-lr-multi.py
@@ -70,7 +70,7 @@ def main(config="../../config.yaml", param="./vehicle_config.yaml", namespace=""
                          input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation('evaluation_0',
-                              runtime_roles=['guest'],
+                              runtime_parties=['guest'],
                               input_data=lr_0.outputs["train_output_data"],
                               predict_column_name='predict_result',
                               metrics=['multi_recall', 'multi_accuracy', 'multi_precision'])
diff --git a/examples/benchmark_quality/lr/pipeline-sshe-lr-binary.py b/examples/benchmark_quality/lr/pipeline-sshe-lr-binary.py
index ae73096e10..a36e012c47 100644
--- a/examples/benchmark_quality/lr/pipeline-sshe-lr-binary.py
+++ b/examples/benchmark_quality/lr/pipeline-sshe-lr-binary.py
@@ -73,7 +73,7 @@ def main(config="../../config.yaml", param="./breast_config.yaml", namespace="")
                   input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation("evaluation_0",
-                              runtime_roles=["guest"],
+                              runtime_parties=["guest"],
                               metrics=["auc", "binary_precision", "binary_accuracy", "binary_recall"],
                               input_data=lr_0.outputs["train_output_data"])
     pipeline.add_task(reader_0)
diff --git a/examples/benchmark_quality/lr/pipeline-sshe-lr-multi.py b/examples/benchmark_quality/lr/pipeline-sshe-lr-multi.py
index 96b79b6253..64bc413fcb 100644
--- a/examples/benchmark_quality/lr/pipeline-sshe-lr-multi.py
+++ b/examples/benchmark_quality/lr/pipeline-sshe-lr-multi.py
@@ -71,7 +71,7 @@ def main(config="../../config.yaml", param="./vehicle_config.yaml", namespace=""
                   input_model=lr_0.outputs["output_model"])
 
     evaluation_0 = Evaluation('evaluation_0',
-                              runtime_roles=['guest'],
+                              runtime_parties=['guest'],
                               input_data=lr_0.outputs["train_output_data"],
                               predict_column_name='predict_result',
                               metrics=['multi_recall', 'multi_accuracy', 'multi_precision'])