diff --git a/gtsam/discrete/tests/testDiscreteBayesTree.cpp b/gtsam/discrete/tests/testDiscreteBayesTree.cpp
index 0288561cd..617eb7c9d 100644
--- a/gtsam/discrete/tests/testDiscreteBayesTree.cpp
+++ b/gtsam/discrete/tests/testDiscreteBayesTree.cpp
@@ -347,26 +347,26 @@ TEST(DiscreteBayesTree, Lookup) {
   EXPECT_LONGS_EQUAL(2, lookup->size());
   auto lookup_x1_a1_x2 = (*lookup)[X(1)]->conditional();
   EXPECT_LONGS_EQUAL(3, lookup_x1_a1_x2->frontals().size());
-  // check that sum is 100
+  // check that sum is 1.0 (not 100, as we now normalize)
   DiscreteValues empty;
-  EXPECT_DOUBLES_EQUAL(100, (*lookup_x1_a1_x2->sum(3))(empty), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*lookup_x1_a1_x2->sum(3))(empty), 1e-9);
   // And that only non-zero reward is for x1 a1 x2 == 0 1 1
-  EXPECT_DOUBLES_EQUAL(100, (*lookup_x1_a1_x2)({{X(1),0},{A(1),1},{X(2),1}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*lookup_x1_a1_x2)({{X(1),0},{A(1),1},{X(2),1}}), 1e-9);
 
   auto lookup_a2_x3 = (*lookup)[X(3)]->conditional();
   // check that the sum depends on x2 and is non-zero only for x2 \in {1,2}
   auto sum_x2 = lookup_a2_x3->sum(2);
   EXPECT_DOUBLES_EQUAL(0, (*sum_x2)({{X(2),0}}), 1e-9);
-  EXPECT_DOUBLES_EQUAL(10, (*sum_x2)({{X(2),1}}), 1e-9);
-  EXPECT_DOUBLES_EQUAL(20, (*sum_x2)({{X(2),2}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*sum_x2)({{X(2),1}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(2.0, (*sum_x2)({{X(2),2}}), 1e-9);
   EXPECT_LONGS_EQUAL(2, lookup_a2_x3->frontals().size());
   // And that the non-zero rewards are for 
   // x2 a2 x3 == 1 1 2
-  EXPECT_DOUBLES_EQUAL(10, (*lookup_a2_x3)({{X(2),1},{A(2),1},{X(3),2}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*lookup_a2_x3)({{X(2),1},{A(2),1},{X(3),2}}), 1e-9);
   // x2 a2 x3 == 2 0 2
-  EXPECT_DOUBLES_EQUAL(10, (*lookup_a2_x3)({{X(2),2},{A(2),0},{X(3),2}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*lookup_a2_x3)({{X(2),2},{A(2),0},{X(3),2}}), 1e-9);
   // x2 a2 x3 == 2 1 2
-  EXPECT_DOUBLES_EQUAL(10, (*lookup_a2_x3)({{X(2),2},{A(2),1},{X(3),2}}), 1e-9);
+  EXPECT_DOUBLES_EQUAL(1.0, (*lookup_a2_x3)({{X(2),2},{A(2),1},{X(3),2}}), 1e-9);
 }
 
 /* ************************************************************************* */
diff --git a/gtsam_unstable/linear/tests/testQPSolver.cpp b/gtsam_unstable/linear/tests/testQPSolver.cpp
index 12bd93416..b307c7302 100644
--- a/gtsam_unstable/linear/tests/testQPSolver.cpp
+++ b/gtsam_unstable/linear/tests/testQPSolver.cpp
@@ -181,7 +181,7 @@ TEST(QPSolver, iterate) {
   QPSolver::State state(currentSolution, VectorValues(), workingSet, false,
                         100);
 
-  int it = 0;
+  // int it = 0;
   while (!state.converged) {
     state = solver.iterate(state);
     // These checks will fail because the expected solutions obtained from
@@ -190,7 +190,7 @@ TEST(QPSolver, iterate) {
     // do not recompute dual variables after every step!!!
     //    CHECK(assert_equal(expected[it], state.values, 1e-10));
     //    CHECK(assert_equal(expectedDuals[it], state.duals, 1e-10));
-    it++;
+    // it++;
   }
 
   CHECK(assert_equal(expected[3], state.values, 1e-10));
diff --git a/python/gtsam/tests/test_DiscreteBayesTree.py b/python/gtsam/tests/test_DiscreteBayesTree.py
index c8a93e63b..2a9b6ea09 100644
--- a/python/gtsam/tests/test_DiscreteBayesTree.py
+++ b/python/gtsam/tests/test_DiscreteBayesTree.py
@@ -128,15 +128,15 @@ class TestDiscreteBayesNet(GtsamTestCase):
         assert lookup.size() == 2
         lookup_x1_a1_x2 = lookup[X(1)].conditional()
         assert lookup_x1_a1_x2.nrFrontals() == 3
-        # Check that sum is 100
+        # Check that sum is 1.0 (not 100, as we now normalize to prevent underflow)
         empty = gtsam.DiscreteValues()
-        self.assertAlmostEqual(lookup_x1_a1_x2.sum(3)(empty), 100)
+        self.assertAlmostEqual(lookup_x1_a1_x2.sum(3)(empty), 1.0)
         # And that only non-zero reward is for x1 a1 x2 == 0 1 1
         values = DiscreteValues()
         values[X(1)] = 0
         values[A(1)] = 1
         values[X(2)] = 1
-        self.assertAlmostEqual(lookup_x1_a1_x2(values), 100)
+        self.assertAlmostEqual(lookup_x1_a1_x2(values), 1.0)
 
         lookup_a2_x3 = lookup[X(3)].conditional()
         # Check that the sum depends on x2 and is non-zero only for x2 in {1, 2}
@@ -145,16 +145,16 @@ class TestDiscreteBayesNet(GtsamTestCase):
         values[X(2)] = 0
         self.assertAlmostEqual(sum_x2(values), 0)
         values[X(2)] = 1
-        self.assertAlmostEqual(sum_x2(values), 10)
+        self.assertAlmostEqual(sum_x2(values), 1.0)  # not 10, as we normalize
         values[X(2)] = 2
-        self.assertAlmostEqual(sum_x2(values), 20)
+        self.assertAlmostEqual(sum_x2(values), 2.0)  # not 20, as we normalize
         assert lookup_a2_x3.nrFrontals() == 2
         # And that the non-zero rewards are for x2 a2 x3 == 1 1 2
         values = DiscreteValues()
         values[X(2)] = 1
         values[A(2)] = 1
         values[X(3)] = 2
-        self.assertAlmostEqual(lookup_a2_x3(values), 10)
+        self.assertAlmostEqual(lookup_a2_x3(values), 1.0)  # not 10...
 
 if __name__ == "__main__":
     unittest.main()