diff --git a/sinabs/backend/dynapcnn/mapping.py b/sinabs/backend/dynapcnn/mapping.py
index 5fefaa0b..36c38ad4 100644
--- a/sinabs/backend/dynapcnn/mapping.py
+++ b/sinabs/backend/dynapcnn/mapping.py
@@ -88,6 +88,7 @@ def __repr__(self):
 
 # graph is list of list of edges. Each edge is
 def edmonds(graph, source, sink, verbose: bool = False):
+    """Use Edmonds-Karp-Algorithm to match software layers to chip layers"""
     graph = deepcopy(graph)
     flow = 0
     while True:
@@ -95,8 +96,8 @@ def edmonds(graph, source, sink, verbose: bool = False):
         q.append(source)
         pred = [None for _ in range(len(graph))]
         while len(q) != 0:
-            cur = q.popleft()
-            for edge in graph[cur]:
+            cur = q.popleft()  # current node index
+            for edge in graph[cur]:  # edges to/from current node
                 if pred[edge.t] is None and edge.t != source and edge.cap > edge.flow:
                     pred[edge.t] = edge
                     q.append(edge.t)
@@ -123,9 +124,12 @@ def edmonds(graph, source, sink, verbose: bool = False):
 def make_flow_graph(
     layer_mapping: List[List[int]], num_layers: int = 9
 ) -> List[List[Edge]]:
-    """Make a flow graph given all possible chip layers for each DynapcnnCompatibleLayer layer.
-    Note that the flows are not computed yet. The flow for the graph generated here needs to be
-    populated by calling the method `edmonds`
+    """
+    Make a bipartite flow graph (flow network) given all possible chip layers
+    for each DynapcnnLayer layer. The goal is to formulate the mapping from
+    software layer to chip layer as a bipartite matching problem. Note that the
+    flows are not computed yet. The flow for the graph generated here needs to
+    be populated by calling the method `edmonds`
 
     Parameters
     ----------