diff --git a/distance.hpp b/distance.hpp
index 54f14c6..b76c04a 100644
--- a/distance.hpp
+++ b/distance.hpp
@@ -66,10 +66,10 @@ static avs::matf32_t avx512_subtract_batch(avs::vecf32_t const &query,
   int32_t const N = data.size();
   int32_t const dim = data[0].size();
   avs::matf32_t result(N, avs::vecf32_t(dim, 0.0f));
-  for (int i = 0; i < N; i++) {
+  for (int32_t i = 0; i < N; i++) {
     float PORTABLE_ALIGN64 tmp[dim];
     avx512_subtract(query.data(), data[i].data(), tmp);
-    for (int k = 0; k < dim; k++) {
+    for (int32_t k = 0; k < dim; k++) {
       result[i][k] = tmp[k];
     }
   }
@@ -104,7 +104,7 @@ static avs::vecf32_t amx_matmul(const int32_t &r, const int32_t &c,
   auto c_mem = dnnl::memory(pd.dst_desc(), engine);
 
   auto prim = dnnl::matmul(pd);
-  std::unordered_map<int, dnnl::memory> args;
+  std::unordered_map<int32_t, dnnl::memory> args;
   args.insert({DNNL_ARG_SRC, a_mem});
   args.insert({DNNL_ARG_WEIGHTS, b_mem});
   args.insert({DNNL_ARG_DST, c_mem});
@@ -112,11 +112,11 @@ static avs::vecf32_t amx_matmul(const int32_t &r, const int32_t &c,
   stream.wait();
 
   read_from_dnnl_memory(dst.data(), c_mem);
-  avs::vecf32_t res(r, 0.0f);
-  for (int i = 0; i < r; i++) {
-    res[i] = dst[i * r + i];
+  avs::vecf32_t result(r, 0.0f);
+  for (int32_t i = 0; i < r; i++) {
+    result[i] = dst[i * r + i];
   }
-  return res;
+  return result;
 }
 
 static matf32_t amx_inner_product(int32_t const &n, int32_t const &oc,
@@ -149,7 +149,7 @@ static matf32_t amx_inner_product(int32_t const &n, int32_t const &oc,
   auto dst_mem = dnnl::memory(pd.dst_desc(), engine);
 
   auto prim = dnnl::inner_product_forward(pd);
-  std::unordered_map<int, dnnl::memory> args;
+  std::unordered_map<int32_t, dnnl::memory> args;
   args.insert({DNNL_ARG_SRC, s_mem});
   args.insert({DNNL_ARG_WEIGHTS, w_mem});
   args.insert({DNNL_ARG_DST, dst_mem});
@@ -158,13 +158,13 @@ static matf32_t amx_inner_product(int32_t const &n, int32_t const &oc,
 
   avs::vecf32_t dst(n * oc, 0.0f);
   read_from_dnnl_memory(dst.data(), dst_mem);
-  avs::matf32_t res(n, avs::vecf32_t(oc, 0.0f));
-  for (int i = 0; i < n; i++) {
-    for (int j = 0; j < oc; j++) {
-      res[i][j] = dst[i * oc + j];
+  avs::matf32_t result(n, avs::vecf32_t(oc, 0.0f));
+  for (int32_t i = 0; i < n; i++) {
+    for (int32_t j = 0; j < oc; j++) {
+      result[i][j] = dst[i * oc + j];
     }
   }
-  return res;
+  return result;
 }
 
 static avs::matf32_t ip_distance_amx(avs::matf32_t const &queries,
@@ -176,13 +176,13 @@ static avs::matf32_t ip_distance_amx(avs::matf32_t const &queries,
   int32_t const ic = queries[0].size();
   avs::vecf32_t queries_1d(n * ic);
   avs::vecf32_t batch_1d(oc * ic);
-  for (int i = 0; i < n; i++) {
-    for (int j = 0; j < ic; j++) {
+  for (int32_t i = 0; i < n; i++) {
+    for (int32_t j = 0; j < ic; j++) {
       queries_1d[i * ic + j] = queries[i][j];
     }
   }
-  for (int i = 0; i < oc; i++) {
-    for (int j = 0; j < ic; j++) {
+  for (int32_t i = 0; i < oc; i++) {
+    for (int32_t j = 0; j < ic; j++) {
       batch_1d[i * ic + j] = batch[i][j];
     }
   }
@@ -197,20 +197,20 @@ static avs::vecf32_t l2_distance_amx(avs::vecf32_t const &query,
   int32_t const dim = batch[0].size();
   avs::matf32_t dis_2d = avx512_subtract_batch(query, batch);
   avs::matf32_t dis_2d_t(dis_2d[0].size(), avs::vecf32_t(dis_2d.size(), 0.0f));
-  for (int i = 0; i < dis_2d_t.size(); i++) {
-    for (int j = 0; j < dis_2d_t[0].size(); j++) {
+  for (int32_t i = 0; i < dis_2d_t.size(); i++) {
+    for (int32_t j = 0; j < dis_2d_t[0].size(); j++) {
       dis_2d_t[i][j] = dis_2d[j][i];
     }
   }
   avs::vecf32_t dis_1d(batch_size * dim);
-  for (int i = 0; i < batch_size; i++) {
-    for (int j = 0; j < dim; j++) {
+  for (int32_t i = 0; i < batch_size; i++) {
+    for (int32_t j = 0; j < dim; j++) {
       dis_1d[i * dim + j] = dis_2d[i][j];
     }
   }
   avs::vecf32_t dis_1d_t(batch_size * dim);
-  for (int i = 0; i < dim; i++) {
-    for (int j = 0; j < batch_size; j++) {
+  for (int32_t i = 0; i < dim; i++) {
+    for (int32_t j = 0; j < batch_size; j++) {
       dis_1d_t[i * batch_size + j] = dis_2d_t[i][j];
     }
   }
@@ -220,25 +220,25 @@ static avs::vecf32_t l2_distance_amx(avs::vecf32_t const &query,
 static float L2Sqr(void const *vec1, void const *vec2, int32_t const &dim) {
   float *v1 = (float *)vec1;
   float *v2 = (float *)vec2;
-  float res = 0;
+  float result = 0;
   for (int32_t i = 0; i < dim; i++) {
     float t = *v1 - *v2;
     v1++;
     v2++;
-    res += t * t;
+    result += t * t;
   }
-  return (res);
+  return (result);
 }
 
 static float InnerProduct(void const *vec1, void const *vec2,
                           int32_t const &dim) {
   float *v1 = (float *)vec1;
   float *v2 = (float *)vec2;
-  float res = 0;
+  float result = 0;
   for (int32_t i = 0; i < dim; i++) {
-    res += ((float *)v1)[i] * ((float *)v2)[i];
+    result += ((float *)v1)[i] * ((float *)v2)[i];
   }
-  return res;
+  return result;
 }
 
 static avs::vecf32_t l2_distance_vanilla(avs::vecf32_t const &query,
@@ -246,12 +246,12 @@ static avs::vecf32_t l2_distance_vanilla(avs::vecf32_t const &query,
                                          dnnl::engine &engine,
                                          dnnl::stream &stream) {
   int32_t const dim = batch[0].size();
-  avs::vecf32_t res(batch.size());
-  for (int i = 0; i < batch.size(); i++) {
+  avs::vecf32_t result(batch.size());
+  for (int32_t i = 0; i < batch.size(); i++) {
     auto d = L2Sqr(query.data(), batch[i].data(), dim);
-    res[i] = d;
+    result[i] = d;
   }
-  return res;
+  return result;
 }
 
 static avs::vecf32_t ip_distance_vanilla(avs::vecf32_t const &query,
@@ -259,12 +259,12 @@ static avs::vecf32_t ip_distance_vanilla(avs::vecf32_t const &query,
                                          dnnl::engine &engine,
                                          dnnl::stream &stream) {
   int32_t const dim = batch[0].size();
-  avs::vecf32_t res(batch.size());
-  for (int i = 0; i < batch.size(); i++) {
+  avs::vecf32_t result(batch.size());
+  for (int32_t i = 0; i < batch.size(); i++) {
     auto d = InnerProduct(query.data(), batch[i].data(), dim);
-    res[i] = d;
+    result[i] = d;
   }
-  return res;
+  return result;
 }
 
 } // namespace avs