diff --git a/tensorflow_privacy/privacy/membership_inference_attack/data_structures_test.py b/tensorflow_privacy/privacy/membership_inference_attack/data_structures_test.py
index 3409328..0f9ffbe 100644
--- a/tensorflow_privacy/privacy/membership_inference_attack/data_structures_test.py
+++ b/tensorflow_privacy/privacy/membership_inference_attack/data_structures_test.py
@@ -21,6 +21,8 @@ from tensorflow_privacy.privacy.membership_inference_attack.data_structures impo
 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import AttackType
 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import RocCurve
 from tensorflow_privacy.privacy.membership_inference_attack.data_structures import SingleAttackResult
+from tensorflow_privacy.privacy.membership_inference_attack.data_structures import SingleSliceSpec
+from tensorflow_privacy.privacy.membership_inference_attack.data_structures import SlicingFeature
 
 
 class AttackInputDataTest(absltest.TestCase):
@@ -106,7 +108,9 @@ class SingleAttackResultTest(absltest.TestCase):
         thresholds=np.array([0, 1, 2]))
 
     result = SingleAttackResult(
-        roc_curve=roc, slice_spec=None, attack_type=AttackType.THRESHOLD_ATTACK)
+        roc_curve=roc,
+        slice_spec=SingleSliceSpec(None),
+        attack_type=AttackType.THRESHOLD_ATTACK)
 
     self.assertEqual(result.get_auc(), 0.5)
 
@@ -118,7 +122,9 @@ class SingleAttackResultTest(absltest.TestCase):
         thresholds=np.array([0, 1, 2]))
 
     result = SingleAttackResult(
-        roc_curve=roc, slice_spec=None, attack_type=AttackType.THRESHOLD_ATTACK)
+        roc_curve=roc,
+        slice_spec=SingleSliceSpec(None),
+        attack_type=AttackType.THRESHOLD_ATTACK)
 
     self.assertEqual(result.get_attacker_advantage(), 0.0)
 
@@ -133,7 +139,7 @@ class AttackResultsTest(absltest.TestCase):
 
     # ROC curve of a perfect classifier
     self.perfect_classifier_result = SingleAttackResult(
-        slice_spec=None,
+        slice_spec=SingleSliceSpec(SlicingFeature.CORRECTLY_CLASSIFIED, True),
         attack_type=AttackType.THRESHOLD_ATTACK,
         roc_curve=RocCurve(
             tpr=np.array([0.0, 1.0, 1.0]),
@@ -142,7 +148,7 @@ class AttackResultsTest(absltest.TestCase):
 
     # ROC curve of a random classifier
     self.random_classifier_result = SingleAttackResult(
-        slice_spec=None,
+        slice_spec=SingleSliceSpec(None),
         attack_type=AttackType.THRESHOLD_ATTACK,
         roc_curve=RocCurve(
             tpr=np.array([0.0, 0.5, 1.0]),
@@ -173,6 +179,32 @@ class AttackResultsTest(absltest.TestCase):
     self.assertEqual(results.get_result_with_max_attacker_advantage(),
                      self.perfect_classifier_result)
 
+  def test_summary_by_slices(self):
+    results = AttackResults(
+        [self.perfect_classifier_result, self.random_classifier_result])
+    self.assertEqual(
+        results.summary(by_slices=True), 'Highest AUC on slice '
+                                         'SingleSliceSpec' +
+        '(SlicingFeature.CORRECTLY_CLASSIFIED=True) achieved by ' +
+        'AttackType.THRESHOLD_ATTACK with an AUC of 1.0\n' +
+        'Highest advantage on ' +
+        'slice SingleSliceSpec(SlicingFeature.CORRECTLY_CLASSIFIED=True) ' +
+        'achieved by AttackType.THRESHOLD_ATTACK with an advantage of 1.0\n' +
+        'Highest AUC on slice SingleSliceSpec(Entire dataset) achieved ' +
+        'by AttackType.THRESHOLD_ATTACK with an AUC of 0.5\n' +
+        'Highest advantage on slice SingleSliceSpec(Entire dataset) achieved ' +
+        'by AttackType.THRESHOLD_ATTACK with an advantage of 0.0')
+
+  def test_summary_without_slices(self):
+    results = AttackResults(
+        [self.perfect_classifier_result, self.random_classifier_result])
+    self.assertEqual(
+        results.summary(by_slices=False),
+        'Highest AUC on slice SingleSliceSpec(Entire dataset) achieved ' +
+        'by AttackType.THRESHOLD_ATTACK with an AUC of 0.5\n' +
+        'Highest advantage on slice SingleSliceSpec(Entire dataset) achieved ' +
+        'by AttackType.THRESHOLD_ATTACK with an advantage of 0.0')
+
 
 if __name__ == '__main__':
   absltest.main()