diff --git a/tests/optimization/__init__.py b/tests/optimization/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/solvers/__init__.py b/tests/solvers/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tests/utils.py b/tests/utils.py
deleted file mode 100644
index 8bb520a..0000000
--- a/tests/utils.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import numpy as np
-import networkx as nx
-from typing import List, Tuple
-
-from mac.utils import select_edges, split_edges, nx_to_mac, mac_to_nx, Edge
-
-def get_split_petersen_graph() -> Tuple[List[Edge], List[Edge], int]:
-    """
-    Get a "split" Petersen graph for testing purposes.
-    Returns:
-        fixed_edges: a chain of edges in the graph.
-        candidate_edges: the remaining edges in the graph.
-        n: the number of nodes in the graph.
-    """
-    G = nx.petersen_graph()
-    n = len(G.nodes())
-
-    # Add a chain
-    for i in range(n-1):
-        if G.has_edge(i+1, i):
-            G.remove_edge(i+1, i)
-            pass
-        if not G.has_edge(i, i+1):
-            G.add_edge(i, i+1)
-            pass
-        pass
-
-    edges = nx_to_mac(G)
-
-    # Split chain and non-chain parts
-    fixed_edges , candidate_edges = split_edges(edges)
-
-    return fixed_edges, candidate_edges, n
-
-def get_split_erdos_renyi_graph(n: int=20, p: float = 0.30) -> Tuple[List[Edge], List[Edge], int]:
-    G = nx.erdos_renyi_graph(n, p)
-
-    for i in range(n-1):
-        if G.has_edge(i+1, i):
-            G.remove_edge(i+1, i)
-        if not G.has_edge(i, i+1):
-            G.add_edge(i, i+1)
-
-    edges = nx_to_mac(G)
-    fixed_edges, candidate_edges = split_edges(edges)
-    return fixed_edges, candidate_edges, n
\ No newline at end of file
diff --git a/tests/utils/__init__.py b/tests/utils/__init__.py
new file mode 100644
index 0000000..e69de29