diff --git a/src/EasyGA.py b/src/EasyGA.py
index f00a29a..a415e42 100644
--- a/src/EasyGA.py
+++ b/src/EasyGA.py
@@ -11,8 +11,8 @@ from initialization.random_initialization import random_initialization
 class GA:
     def __init__(self):
         # Default variables
-        self.domain = None
-        self.new_range = None
+        self.chromosome_impl = None
+        self.gene_impl = None
         self.population = None
         self.generations = 3
         self.chromosome_length = 3
@@ -30,8 +30,8 @@ class GA:
         self.population = self.initialization_impl(
         self.population_size,
         self.chromosome_length,
-        self.domain,
-        self.new_range)
+        self.chromosome_impl,
+        self.gene_impl)
 
     def evolve():
         # If you just want to evolve through all generations
diff --git a/src/initialization/random_initialization.py b/src/initialization/random_initialization.py
index 4c4e048..6484e43 100644
--- a/src/initialization/random_initialization.py
+++ b/src/initialization/random_initialization.py
@@ -3,7 +3,7 @@ from .population_structure.population import population as create_population
 from .chromosome_structure.chromosome import chromosome as create_chromosome
 from .gene_structure.gene import gene as create_gene
 
-def random_initialization(population_size, chromosome_length, domain, new_range):
+def random_initialization(population_size, chromosome_length, chromosome_impl, gene_impl):
     # Create the population object
     population = create_population()
     # Fill the population with chromosomes
@@ -11,14 +11,14 @@ def random_initialization(population_size, chromosome_length, domain, new_range)
         chromosome = create_chromosome()
         #Fill the Chromosome with genes
         for j in range(chromosome_length):
-            if domain != None:
+            if chromosome_impl != None:
                 # Each chromosome location is specified with its own function
-                chromosome.add_gene(create_gene(domain(j)))
+                chromosome.add_gene(create_gene(chromosome_impl(j)))
                 # Will break if chromosome_length != lists in domain
-            elif new_range != None:
-                # new_rnage = [range function,lowerbound,upperbound]
-                function = new_range[0]
-                chromosome.add_gene(create_gene(function(new_range[1],new_range[2])))
+            elif gene_impl != None:
+                # gene_impl = [range function,lowerbound,upperbound]
+                function = gene_impl[0]
+                chromosome.add_gene(create_gene(function(gene_impl[1],gene_impl[2])))
             else:
                 #Exit because either were not specified
                 print("Your domain or range were not specified")
diff --git a/src/run_testing.py b/src/run_testing.py
index 442d58f..e05ac52 100644
--- a/src/run_testing.py
+++ b/src/run_testing.py
@@ -1,26 +1,20 @@
 import EasyGA
 import random
-
 # Create the Genetic algorithm
 ga = EasyGA.GA()
 
 def user_gene_domain(gene_index):
     """Each gene index is assosiated to its index in the chromosome"""
-    domain = [
-    random.randrange(1,100,5),
+    chromosome = [
+    random.randrange(1,100),
     random.uniform(10,5),
     random.choice(["up","down"])
     ]
-    return domain[gene_index]
-
-print(user_gene_domain(0))
+    return chromosome[gene_index]
 
 # If the user wants to use a domain
-ga.domain = user_gene_domain
-# If the user wants to use a custom range
-#ga.new_range = [random.randrange,1,100,None]
+ga.chromosome_impl = user_gene_domain
 
 ga.initialize()
 
-#ga.population.print_all()
-
+ga.population.print_all()