diff --git a/test/datasets/test_squad1.py b/test/datasets/test_squad.py
similarity index 69%
rename from test/datasets/test_squad1.py
rename to test/datasets/test_squad.py
index 75f1f61639..d44b6637f1 100644
--- a/test/datasets/test_squad1.py
+++ b/test/datasets/test_squad.py
@@ -7,11 +7,12 @@
 from random import randint
 from unittest.mock import patch
 
-from parameterized import parameterized
 from torchtext.data.datasets_utils import _ParseSQuADQAData
 from torchtext.datasets.squad1 import SQuAD1
+from torchtext.datasets.squad2 import SQuAD2
 
 from ..common.case_utils import TempDirMixin, zip_equal
+from ..common.parameterized_utils import nested_params
 from ..common.torchtext_test_case import TorchtextTestCase
 
 
@@ -44,15 +45,20 @@ def _get_mock_json_data():
     return mock_json_data
 
 
-def _get_mock_dataset(root_dir):
+def _get_mock_dataset(root_dir, base_dir_name):
     """
     root_dir: directory to the mocked dataset
     """
-    base_dir = os.path.join(root_dir, "SQuAD1")
+    base_dir = os.path.join(root_dir, base_dir_name)
     os.makedirs(base_dir, exist_ok=True)
 
+    if base_dir_name == SQuAD1.__name__:
+        file_names = ("train-v1.1.json", "dev-v1.1.json")
+    else:
+        file_names = ("train-v2.0.json", "dev-v2.0.json")
+
     mocked_data = defaultdict(list)
-    for file_name in ("train-v1.1.json", "dev-v1.1.json"):
+    for file_name in file_names:
         txt_file = os.path.join(base_dir, file_name)
         with open(txt_file, "w") as f:
             mock_json_data = _get_mock_json_data()
@@ -67,7 +73,7 @@ def _get_mock_dataset(root_dir):
     return mocked_data
 
 
-class TestSQuAD1(TempDirMixin, TorchtextTestCase):
+class TestSQuAD(TempDirMixin, TorchtextTestCase):
     root_dir = None
     samples = []
 
@@ -75,7 +81,6 @@ class TestSQuAD1(TempDirMixin, TorchtextTestCase):
     def setUpClass(cls):
         super().setUpClass()
         cls.root_dir = cls.get_base_temp_dir()
-        cls.samples = _get_mock_dataset(cls.root_dir)
         cls.patcher = patch(
             "torchdata.datapipes.iter.util.cacheholder._hash_check", return_value=True
         )
@@ -86,19 +91,24 @@ def tearDownClass(cls):
         cls.patcher.stop()
         super().tearDownClass()
 
-    @parameterized.expand(["train", "dev"])
-    def test_squad1(self, split):
-        dataset = SQuAD1(root=self.root_dir, split=split)
-
+    @nested_params([SQuAD1, SQuAD2], ["train", "dev"])
+    def test_squad(self, squad_dataset, split):
+        expected_samples = _get_mock_dataset(self.root_dir, squad_dataset.__name__)[
+            split
+        ]
+        dataset = squad_dataset(root=self.root_dir, split=split)
         samples = list(dataset)
-        expected_samples = self.samples[split]
+
         for sample, expected_sample in zip_equal(samples, expected_samples):
             self.assertEqual(sample, expected_sample)
 
-    @parameterized.expand(["train", "dev"])
-    def test_squad1_split_argument(self, split):
-        dataset1 = SQuAD1(root=self.root_dir, split=split)
-        (dataset2,) = SQuAD1(root=self.root_dir, split=(split,))
+    @nested_params([SQuAD1, SQuAD2], ["train", "dev"])
+    def test_squad_split_argument(self, squad_dataset, split):
+        # call `_get_mock_dataset` to create mock dataset files
+        _ = _get_mock_dataset(self.root_dir, squad_dataset.__name__)
+
+        dataset1 = squad_dataset(root=self.root_dir, split=split)
+        (dataset2,) = squad_dataset(root=self.root_dir, split=(split,))
 
         for d1, d2 in zip_equal(dataset1, dataset2):
             self.assertEqual(d1, d2)