diff --git a/test_synthetic.py b/test_synthetic.py
index 56b7106..7c641ef 100644
--- a/test_synthetic.py
+++ b/test_synthetic.py
@@ -44,6 +44,11 @@ def map_randomly(Xd, fXd):
     for x in Xd:
         y = random.choice(fXd)
         f[x] = y
+
+    # ensure that f is not a constant function
+    if len(set(f.values())) == 1:
+        f = map_randomly(Xd, fXd)
+    assert len(set(f.values())) != 1
     return f
 
 
@@ -181,30 +186,55 @@ def _decision_rate(srcX):
     #                "CISC", "DC", "DR"], "decision rate", "accuracy", "decision rate versus accuracy", "dec_rate_%sX.png" % srcX)
 
 
+def are_disjoint(sets):
+    disjoint = True
+    union = set()
+    for s in sets:
+        for x in s:
+            if x in union:
+                disjoint = False
+                break
+            union.add(x)
+    return disjoint
+
+
 def test_accuracy():
     nsim = 1000
-    size = 5000
+    size = 1000
     level = 0.01
     suppfX = range(-7, 8)
     srcsX = ["uniform", "binomial", "negativeBinomial",
              "geometric", "hypergeometric", "poisson", "multinomial"]
-    print "-" * 64
+    print "-" * 70
     print "%18s%10s%10s%10s%10s%10s" % ("TYPE_X", "DC", "DR", "CISC", "CRISPE", "CRISP")
-    print "-" * 64
+    print "-" * 70
     sys.stdout.flush()
-
     fp = open("results/acc-dtype.dat", "w")
     fp.write("%s\t%s\t%s\t%s\t%s\t%s\n" %
              ("dtype", "dc", "dr", "cisc", "crispe", "crisp"))
     for srcX in srcsX:
+        nsamples = 0
         nc_dc, nc_dr, nc_cisc, nc_crispe, nc_crisp = 0, 0, 0, 0, 0
-        for k in xrange(nsim):
+        while nsamples < nsim:
             X = generate_X(srcX, size)
             suppX = list(set(X))
             f = map_randomly(suppX, suppfX)
             N = generate_additive_N(size)
             Y = [f[X[i]] + N[i] for i in xrange(size)]
 
+            # check if f(x) + supp N are disjoint for x in domx
+            suppN = set(N)
+            decomps = []
+            for x in suppX:
+                fx = f[x]
+                sum_fx_suppN = set([fx + n for n in suppN])
+                decomps.append(sum_fx_suppN)
+
+            non_overlapping_noise = are_disjoint(decomps)
+            if non_overlapping_noise:
+                continue
+
+            nsamples += 1
             dc_score = dc(dc_compat(X), dc_compat(Y))
             dr_score = dr(X, Y, level)
             cisc_score = cisc(X, Y)
@@ -217,6 +247,8 @@ def test_accuracy():
             nc_crispe += int(crispe_score[0] < crispe_score[1])
             nc_crisp += int(crisp_score[0] < crisp_score[1])
 
+        assert nsamples == nsim
+
         acc_dc = nc_dc * 100 / nsim
         acc_dr = nc_dr * 100 / nsim
         acc_cisc = nc_cisc * 100 / nsim
@@ -226,7 +258,7 @@ def test_accuracy():
         sys.stdout.flush()
         fp.write("%s\t%.2f\t%.2f\t%.2f\t%.2f\t%.2f\n" %
                  (srcX, acc_dc, acc_dr, acc_cisc, acc_crispe, acc_crisp))
-    print "-" * 58
+    print "-" * 70
     sys.stdout.flush()
     fp.close()
 
@@ -529,9 +561,9 @@ def test_hypercompression():
 
 
 def test_sample_size():
-    nsim = 5000
+    nsim = 500
     level = 0.05
-    sizes = [50, 100, 500, 1000, 2500, 5000]
+    sizes = [100, 500, 1000, 2500, 5000]
     suppfX = range(-7, 8)
     srcX = "geometric"
 
@@ -539,8 +571,7 @@ def test_sample_size():
     diffs = []
     fp.write("%s\t%s\t%s\t%s\t%s\t%s\n" %
              ("size", "dc", "dr", "cisc", "crispe", "crisp"))
-    print "%s\t%s\t%s\t%s\t%s\t%s\n" %
-        ("size", "dc", "dr", "cisc", "crispe", "crisp")
+    print "%s\t%s\t%s\t%s\t%s\t%s" % ("size", "dc", "dr", "cisc", "crispe", "crisp")
     sys.stdout.flush()
     # progress(0, len(sizes))
     for k, size in enumerate(sizes):