diff --git a/gtsam/discrete/tests/testDiscreteBayesTree.cpp b/gtsam/discrete/tests/testDiscreteBayesTree.cpp
index 95d6f0370..bc205c96c 100644
--- a/gtsam/discrete/tests/testDiscreteBayesTree.cpp
+++ b/gtsam/discrete/tests/testDiscreteBayesTree.cpp
@@ -28,7 +28,7 @@
 #include <vector>
 
 using namespace gtsam;
-static constexpr bool debug = false;
+static constexpr bool debug = true;
 
 /* ************************************************************************* */
 struct TestFixture {
@@ -186,11 +186,11 @@ TEST(DiscreteBayesTree, Shortcuts) {
   shortcut = clique->shortcut(R, EliminateDiscrete);
   DOUBLES_EQUAL(joint_8_11_12_13 / joint_11_13, shortcut.evaluate(all1), 1e-9);
 
-  // calculate all shortcuts to root
-  DiscreteBayesTree::Nodes cliques = self.bayesTree->nodes();
-  for (auto clique : cliques) {
-    DiscreteBayesNet shortcut = clique.second->shortcut(R, EliminateDiscrete);
-    if (debug) {
+  if (debug) {
+    // print all shortcuts to root
+    DiscreteBayesTree::Nodes cliques = self.bayesTree->nodes();
+    for (auto clique : cliques) {
+      DiscreteBayesNet shortcut = clique.second->shortcut(R, EliminateDiscrete);
       clique.second->conditional_->printSignature();
       shortcut.print("shortcut:");
     }
@@ -202,6 +202,7 @@ TEST(DiscreteBayesTree, Shortcuts) {
 TEST(DiscreteBayesTree, MarginalFactors) {
   TestFixture self;
 
+  // Caclulate marginals with brute force enumeration.
   Vector marginals = Vector::Zero(15);
   for (size_t i = 0; i < self.assignments.size(); ++i) {
     DiscreteValues& x = self.assignments[i];
@@ -287,6 +288,8 @@ TEST(DiscreteBayesTree, Joints) {
 TEST(DiscreteBayesTree, Dot) {
   TestFixture self;
   std::string actual = self.bayesTree->dot();
+  // print actual:
+  if (debug) std::cout << actual << std::endl;
   EXPECT(actual ==
          "digraph G{\n"
          "0[label=\"13, 11, 6, 7\"];\n"
@@ -374,18 +377,18 @@ TEST(DiscreteBayesTree, Lookup) {
 TEST(DiscreteBayesTree, DirectFromCliques) {
   // Create a BayesNet
   DiscreteBayesNet bayesNet;
-  DiscreteKey key0(0, 2), key1(1, 2), key2(2, 2);
-  bayesNet.add(key0 % "1/3");
-  bayesNet.add(key1 | key0 = "1/3 3/1");
-  bayesNet.add(key2 | key1 = "3/1 3/1");
+  DiscreteKey A(0, 2), B(1, 2), C(2, 2);
+  bayesNet.add(A % "1/3");
+  bayesNet.add(B | A = "1/3 3/1");
+  bayesNet.add(C | B = "3/1 3/1");
 
   // Create cliques directly
   auto clique2 = std::make_shared<DiscreteBayesTree::Clique>(
-      std::make_shared<DiscreteConditional>(key2 | key1 = "3/1 3/1"));
+      std::make_shared<DiscreteConditional>(C | B = "3/1 3/1"));
   auto clique1 = std::make_shared<DiscreteBayesTree::Clique>(
-      std::make_shared<DiscreteConditional>(key1 | key0 = "1/3 3/1"));
+      std::make_shared<DiscreteConditional>(B | A = "1/3 3/1"));
   auto clique0 = std::make_shared<DiscreteBayesTree::Clique>(
-      std::make_shared<DiscreteConditional>(key0 % "1/3"));
+      std::make_shared<DiscreteConditional>(A % "1/3"));
 
   // Create a BayesTree
   DiscreteBayesTree bayesTree;
@@ -395,13 +398,13 @@ TEST(DiscreteBayesTree, DirectFromCliques) {
 
   // Check that the BayesTree is correct
   DiscreteValues values;
-  values[0] = 1;
-  values[1] = 1;
-  values[2] = 1;
+  values[A.first] = 1;
+  values[A.first] = 1;
+  values[A.first] = 1;
 
-  double expected = bayesNet.evaluate(values);
-  double actual = bayesTree.evaluate(values);
-  DOUBLES_EQUAL(expected, actual, 1e-9);
+  // Regression
+  double expected = .046875;
+  DOUBLES_EQUAL(expected, bayesTree.evaluate(values), 1e-9);
 }
 
 /* ************************************************************************* */
diff --git a/python/gtsam/tests/test_DiscreteBayesTree.py b/python/gtsam/tests/test_DiscreteBayesTree.py
index d327b5a1b..e8943fc80 100644
--- a/python/gtsam/tests/test_DiscreteBayesTree.py
+++ b/python/gtsam/tests/test_DiscreteBayesTree.py
@@ -160,15 +160,15 @@ class TestDiscreteBayesNet(GtsamTestCase):
         """Test creating a Bayes tree directly from cliques."""
         # Create a BayesNet
         bayesNet = DiscreteBayesNet()
-        key0, key1, key2 = (0, 2), (1, 2), (2, 2)
-        bayesNet.add(key0, "1/3")
-        bayesNet.add(key1, [key0], "1/3 3/1")
-        bayesNet.add(key2, [key1], "3/1 3/1")
+        A, B, C = (0, 2), (1, 2), (2, 2)
+        bayesNet.add(A, "1/3")
+        bayesNet.add(B, [A], "1/3 3/1")
+        bayesNet.add(C, [B], "3/1 3/1")
 
         # Create cliques directly
-        clique2 = DiscreteBayesTreeClique(DiscreteConditional(key2, [key1], "3/1 3/1"))
-        clique1 = DiscreteBayesTreeClique(DiscreteConditional(key1, [key0], "1/3 3/1"))
-        clique0 = DiscreteBayesTreeClique(DiscreteConditional(key0, "1/3"))
+        clique2 = DiscreteBayesTreeClique(DiscreteConditional(C, [B], "3/1 3/1"))
+        clique1 = DiscreteBayesTreeClique(DiscreteConditional(B, [A], "1/3 3/1"))
+        clique0 = DiscreteBayesTreeClique(DiscreteConditional(A, "1/3"))
 
         # Create a BayesTree
         bayesTree = gtsam.DiscreteBayesTree()
@@ -182,9 +182,9 @@ class TestDiscreteBayesNet(GtsamTestCase):
         values[1] = 1
         values[2] = 1
 
-        expected = bayesNet.evaluate(values)
-        actual = bayesTree.evaluate(values)
-        self.assertAlmostEqual(expected, actual, places=9)
+        # regression
+        expected = .046875
+        self.assertAlmostEqual(expected, bayesNet.evaluate(values))
 
 
 if __name__ == "__main__":