diff --git a/redblackgraph/reference/calc_relationship.py b/redblackgraph/reference/calc_relationship.py
index 24db15c..24a5821 100644
--- a/redblackgraph/reference/calc_relationship.py
+++ b/redblackgraph/reference/calc_relationship.py
@@ -25,7 +25,7 @@ def lookup_relationship(da: int, db: int) -> str:
     This is a very rudimentary implementation of a Consanguinity lookup and doesn't handle many
     cases correctly.
     :param da: generational distance from u to common ancestor
-    :param db: generational distance from v to common ancester
+    :param db: generational distance from v to common ancestor
     :return: a string designating relationship
     '''
     removal = abs(da - db)
diff --git a/redblackgraph/reference/rbg_math.py b/redblackgraph/reference/rbg_math.py
index 7addce6..cf5cb0d 100644
--- a/redblackgraph/reference/rbg_math.py
+++ b/redblackgraph/reference/rbg_math.py
@@ -12,7 +12,7 @@ def MSB(x: int) -> int:
 
 def avos_sum(x: int, y: int) -> int:
     '''
-    The avos sum is the non-zero minumum of x and y
+    The avos sum is the non-zero minimum of x and y
     :param x: operand 1
     :param y: operand 2
     :return: avos sum
diff --git a/redblackgraph/sparse/csgraph/_rbg_math.pxi b/redblackgraph/sparse/csgraph/_rbg_math.pxi
index d5ef712..4915da2 100644
--- a/redblackgraph/sparse/csgraph/_rbg_math.pxi
+++ b/redblackgraph/sparse/csgraph/_rbg_math.pxi
@@ -17,7 +17,7 @@ cdef inline bint avos_lt(DTYPE_t x, DTYPE_t y):
 
 cdef inline DTYPE_t avos_sum(DTYPE_t x, DTYPE_t y):
     '''
-    The avos sum is the non-zero minumum of x and y
+    The avos sum is the non-zero minimum of x and y
     :param x: operand 1
     :param y: operand 2
     :return: avos sum
diff --git a/redblackgraph/util/graph_builder.py b/redblackgraph/util/graph_builder.py
index 6c7d848..b211c18 100644
--- a/redblackgraph/util/graph_builder.py
+++ b/redblackgraph/util/graph_builder.py
@@ -45,7 +45,7 @@ def init_builder(self, nv: int, ne: int):
     def get_ordering(self) -> Sequence[int]:
         if self.graph is None:
             self.graph = rb.rb_matrix(coo_matrix((self.val, (self.row, self.col)), shape=(self.nv, self.nv)))
-        
+
         # For very large graphs, skip canonical ordering to avoid memory issues
         # TODO: Implement sparse transitive closure or alternative ordering method
         if self.nv > self.sparse_threshold:
@@ -56,7 +56,7 @@ def get_ordering(self) -> Sequence[int]:
             )
             # Return identity ordering (or could use topological sort if available)
             return list(range(self.nv))
-        
+
         start_time = time.time()
         print(f"Computing transitive closure...")
         closure = self.graph.transitive_closure().W