- Fix incorrect printf format specifier (-Wformat)
* fann.c: In function ‘fann_print_connections’:
* fann.c:889:11: warning: format ‘%d’ expects argument of type ‘int’, but argument 2 has type ‘long int’ [-Wformat=]
*     printf("L %3d / N %4d %s\n", layer_it - ann->first_layer,

- Fix erroneous memset call
* md5.c: In function ‘MD5Final’:
* md5.c:152:26: warning: argument to ‘sizeof’ in ‘memset’ call is the same expression as the destination; did you mean to dereference it? [-Wsizeof-pointer-memaccess]
*      memset(ctx, 0, sizeof(ctx));        /* In case it's sensitive */

--- a/fann-2.1.0/fann.c
+++ b/fann-2.1.0/fann.c
@@ -886,7 +886,7 @@
 					neurons[ann->connections[i] - ann->first_layer->first_neuron] = (char)('A' + value);
 				}
 			}
-			printf("L %3d / N %4d %s\n", layer_it - ann->first_layer,
+			printf("L %3ld / N %4ld %s\n", layer_it - ann->first_layer,
 				   neuron_it - ann->first_layer->first_neuron, neurons);
 		}
 	}
@@ -987,12 +987,12 @@
 	{
 		if(ann->network_type == FANN_NETTYPE_SHORTCUT)
 		{
-			printf("  Hidden layer                       :%4d neurons, 0 bias\n",
+			printf("  Hidden layer                       :%4ld neurons, 0 bias\n",
 				   layer_it->last_neuron - layer_it->first_neuron);
 		}
 		else
 		{
-			printf("  Hidden layer                       :%4d neurons, 1 bias\n",
+			printf("  Hidden layer                       :%4ld neurons, 1 bias\n",
 				   layer_it->last_neuron - layer_it->first_neuron - 1);
 		}
 	}
--- a/fann-2.1.0/fann_io.c
+++ b/fann-2.1.0/fann_io.c
@@ -174,7 +174,7 @@
 #endif
 
 	/* Save network parameters */
-	fprintf(conf, "num_layers=%u\n", ann->last_layer - ann->first_layer);
+	fprintf(conf, "num_layers=%ld\n", ann->last_layer - ann->first_layer);
 	fprintf(conf, "learning_rate=%f\n", ann->learning_rate);
 	fprintf(conf, "connection_rate=%f\n", ann->connection_rate);
 	fprintf(conf, "network_type=%u\n", ann->network_type);
@@ -236,7 +236,7 @@
 	for(layer_it = ann->first_layer; layer_it != ann->last_layer; layer_it++)
 	{
 		/* the number of neurons in the layers (in the last layer, there is always one too many neurons, because of an unused bias) */
-		fprintf(conf, "%u ", layer_it->last_neuron - layer_it->first_neuron);
+		fprintf(conf, "%ld ", layer_it->last_neuron - layer_it->first_neuron);
 	}
 	fprintf(conf, "\n");
 
@@ -316,14 +316,14 @@
 		if(save_as_fixed)
 		{
 			/* save the connection "(source weight) " */
-			fprintf(conf, "(%u, %d) ",
+			fprintf(conf, "(%ld, %d) ",
 					connected_neurons[i] - first_neuron,
 					(int) floor((weights[i] * fixed_multiplier) + 0.5));
 		}
 		else
 		{
 			/* save the connection "(source weight) " */
-			fprintf(conf, "(%u, " FANNPRINTF ") ", connected_neurons[i] - first_neuron, weights[i]);
+			fprintf(conf, "(%ld, " FANNPRINTF ") ", connected_neurons[i] - first_neuron, weights[i]);
 		}
 #else
 		/* save the connection "(source weight) " */
--- a/CommonSource/Utilities/md5.c
+++ b/CommonSource/Utilities/md5.c
@@ -149,7 +149,7 @@
     MD5Transform(ctx->buf, (uint32 *) ctx->in);
     byteReverse((unsigned char *) ctx->buf, 4);
     memcpy(digest, ctx->buf, 16);
-    memset(ctx, 0, sizeof(ctx));        /* In case it's sensitive */
+    memset(ctx, 0, sizeof(*ctx));        /* In case it's sensitive */
 }