diff --git a/nalgebra-sparse/src/ops/impl_std_ops.rs b/nalgebra-sparse/src/ops/impl_std_ops.rs
index 17f357a6..34a7bcf5 100644
--- a/nalgebra-sparse/src/ops/impl_std_ops.rs
+++ b/nalgebra-sparse/src/ops/impl_std_ops.rs
@@ -1,12 +1,11 @@
 use crate::csr::CsrMatrix;
 
 use std::ops::{Add, Mul};
-use crate::ops::serial::{spadd_csr, spadd_build_pattern, spmm_pattern, spmm_csr};
+use crate::ops::serial::{spadd_csr, spadd_pattern, spmm_pattern, spmm_csr};
 use nalgebra::{ClosedAdd, ClosedMul, Scalar};
 use num_traits::{Zero, One};
 use std::sync::Arc;
 use crate::ops::Transpose;
-use crate::pattern::SparsityPattern;
 
 impl<'a, T> Add<&'a CsrMatrix<T>> for &'a CsrMatrix<T>
 where
@@ -17,8 +16,7 @@ where
     type Output = CsrMatrix<T>;
 
     fn add(self, rhs: &'a CsrMatrix<T>) -> Self::Output {
-        let mut pattern = SparsityPattern::new(self.nrows(), self.ncols());
-        spadd_build_pattern(&mut pattern, self.pattern(), rhs.pattern());
+        let pattern = spadd_pattern(self.pattern(), rhs.pattern());
         let values = vec![T::zero(); pattern.nnz()];
         // We are giving data that is valid by definition, so it is safe to unwrap below
         let mut result = CsrMatrix::try_from_pattern_and_values(Arc::new(pattern), values)
diff --git a/nalgebra-sparse/src/ops/serial/pattern.rs b/nalgebra-sparse/src/ops/serial/pattern.rs
index 2e442cc0..39b8a1c1 100644
--- a/nalgebra-sparse/src/ops/serial/pattern.rs
+++ b/nalgebra-sparse/src/ops/serial/pattern.rs
@@ -1,6 +1,5 @@
 use crate::pattern::SparsityPattern;
 
-use std::mem::swap;
 use std::iter;
 
 /// Sparse matrix addition pattern construction, `C <- A + B`.
@@ -9,21 +8,15 @@ use std::iter;
 /// The patterns are assumed to have the same major and minor dimensions. In other words,
 /// both patterns `A` and `B` must both stem from the same kind of compressed matrix:
 /// CSR or CSC.
-/// TODO: Explain that output pattern is only used to avoid allocations
-pub fn spadd_build_pattern(pattern: &mut SparsityPattern,
-                           a: &SparsityPattern,
-                           b: &SparsityPattern)
+pub fn spadd_pattern(a: &SparsityPattern,
+                     b: &SparsityPattern) -> SparsityPattern
 {
     // TODO: Proper error messages
-    assert_eq!(a.major_dim(), b.major_dim());
-    assert_eq!(a.minor_dim(), b.minor_dim());
+    assert_eq!(a.major_dim(), b.major_dim(), "Patterns must have identical major dimensions.");
+    assert_eq!(a.minor_dim(), b.minor_dim(), "Patterns must have identical minor dimensions.");
 
-    let input_pattern = pattern;
-    let mut temp_pattern = SparsityPattern::new(a.major_dim(), b.minor_dim());
-    swap(input_pattern, &mut temp_pattern);
-    let (mut offsets, mut indices) = temp_pattern.disassemble();
-
-    offsets.clear();
+    let mut offsets = Vec::new();
+    let mut indices = Vec::new();
     offsets.reserve(a.major_dim() + 1);
     indices.clear();
 
@@ -37,10 +30,9 @@ pub fn spadd_build_pattern(pattern: &mut SparsityPattern,
     }
 
     // TODO: Consider circumventing format checks? (requires unsafe, should benchmark first)
-    let mut new_pattern = SparsityPattern::try_from_offsets_and_indices(
+    SparsityPattern::try_from_offsets_and_indices(
         a.major_dim(), a.minor_dim(), offsets, indices)
-        .expect("Pattern must be valid by definition");
-    swap(input_pattern, &mut new_pattern);
+        .expect("Internal error: Pattern must be valid by definition")
 }
 
 /// Sparse matrix multiplication pattern construction, `C <- A * B`.
diff --git a/nalgebra-sparse/tests/unit_tests/ops.rs b/nalgebra-sparse/tests/unit_tests/ops.rs
index d5f2bba8..16482171 100644
--- a/nalgebra-sparse/tests/unit_tests/ops.rs
+++ b/nalgebra-sparse/tests/unit_tests/ops.rs
@@ -1,6 +1,6 @@
 use crate::common::{csr_strategy, PROPTEST_MATRIX_DIM, PROPTEST_MAX_NNZ,
                     PROPTEST_I32_VALUE_STRATEGY};
-use nalgebra_sparse::ops::serial::{spmm_csr_dense, spadd_build_pattern, spmm_pattern, spadd_csr, spmm_csr};
+use nalgebra_sparse::ops::serial::{spmm_csr_dense, spadd_pattern, spmm_pattern, spadd_csr, spmm_csr};
 use nalgebra_sparse::ops::{Transpose};
 use nalgebra_sparse::csr::CsrMatrix;
 use nalgebra_sparse::proptest::{csr, sparsity_pattern};
@@ -88,8 +88,7 @@ fn spadd_csr_args_strategy() -> impl Strategy<Value=SpaddCsrArgs<i32>> {
 
     spadd_build_pattern_strategy()
         .prop_flat_map(move |(a_pattern, b_pattern)| {
-            let mut c_pattern = SparsityPattern::new(a_pattern.major_dim(), b_pattern.major_dim());
-            spadd_build_pattern(&mut c_pattern, &a_pattern, &b_pattern);
+            let c_pattern = spadd_pattern(&a_pattern, &b_pattern);
 
             let a_values = vec![value_strategy.clone(); a_pattern.nnz()];
             let c_values = vec![value_strategy.clone(); c_pattern.nnz()];
@@ -248,11 +247,10 @@ proptest! {
     }
 
     #[test]
-    fn spadd_build_pattern_test((c, (a, b)) in (pattern_strategy(), spadd_build_pattern_strategy()))
+    fn spadd_pattern_test((a, b) in spadd_build_pattern_strategy())
     {
-        // (a, b) are dimensionally compatible patterns, whereas c is an *arbitrary* pattern
-        let mut pattern_result = c.clone();
-        spadd_build_pattern(&mut pattern_result, &a, &b);
+        // (a, b) are dimensionally compatible patterns
+        let pattern_result = spadd_pattern(&a, &b);
 
         // To verify the pattern, we construct CSR matrices with positive integer entries
         // corresponding to a and b, and convert them to dense matrices.