diff --git a/sw/main.py b/sw/main.py
index 7786cc8..53c8a15 100644
--- a/sw/main.py
+++ b/sw/main.py
@@ -16,7 +16,7 @@ def test_decoders(G, decoders: typing.List) -> pd.DataFrame:
     k, n = G.shape
     x = np.zeros(n)  # All-zeros assumption
 
-    SNRs = np.linspace(1, 8, 8)
+    SNRs = np.linspace(1, 7, 7)
     data = pd.DataFrame({"SNR": SNRs})
 
     start_time = default_timer()
@@ -26,7 +26,7 @@ def test_decoders(G, decoders: typing.List) -> pd.DataFrame:
         _, BERs_sd = simulations.test_decoder(x,
                                               decoder=decoder,
                                               SNRs=SNRs,
-                                              target_bit_errors=100,
+                                              target_frame_errors=100,
                                               N_max=50000)
 
         data[f"BER_{decoder_name}"] = BERs_sd
@@ -91,7 +91,7 @@ def main():
         H = codes.get_systematic_H(G)
 
         decoders = {
-            "naive_soft_decision": maximum_likelihood.MLDecoder(G, H),
+            "ML": maximum_likelihood.MLDecoder(G, H),
             "proximal_0_01": proximal.ProximalDecoder(H, gamma=0.01),
             "proximal_0_05": proximal.ProximalDecoder(H, gamma=0.05),
             "proximal_0_15": proximal.ProximalDecoder(H, gamma=0.15),
diff --git a/sw/utility/simulations.py b/sw/utility/simulations.py
index 75ed831..9ed9141 100644
--- a/sw/utility/simulations.py
+++ b/sw/utility/simulations.py
@@ -21,7 +21,7 @@ def count_bit_errors(d: np.array, d_hat: np.array) -> int:
 def test_decoder(x: np.array,
                  decoder: typing.Any,
                  SNRs: typing.Sequence[float] = np.linspace(1, 7, 7),
-                 target_bit_errors: int = 100,
+                 target_frame_errors: int = 100,
                  N_max: int = 10000) \
         -> typing.Tuple[np.array, np.array]:
     """Calculate the Bit Error Rate (BER) for a given decoder for a number of SNRs.
@@ -31,7 +31,7 @@ def test_decoder(x: np.array,
     :param x: Codeword to be sent (Element of [0, 1]^n)
     :param decoder: Instance of the decoder to be tested
     :param SNRs: List of SNRs for which the BER should be calculated
-    :param target_bit_errors: Number of bit errors after which to stop the simulation
+    :param target_frame_errors: Number of frame errors after which to stop the simulation
     :param N_max: Maximum number of iterations to perform for each SNR
     :return: Tuple of numpy arrays of the form (SNRs, BERs)
     """
@@ -46,6 +46,7 @@ def test_decoder(x: np.array,
 
         total_bit_errors = 0
         total_bits = 0
+        total_frame_errors = 0
 
         for n in tqdm(range(N_max), desc=f"Simulating for SNR = {SNR} dB",
                       position=1,
@@ -58,8 +59,9 @@ def test_decoder(x: np.array,
 
             total_bit_errors += count_bit_errors(x, x_hat)
             total_bits += x.size
+            total_frame_errors += 1 if total_bit_errors > 0 else 0
 
-            if total_bit_errors >= target_bit_errors:
+            if total_frame_errors >= target_frame_errors:
                 break
 
         BERs.append(total_bit_errors / total_bits)