diff --git a/CHANGELOG.md b/CHANGELOG.md
index 8e367a99b..cbf077ed1 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -386,12 +386,12 @@ Changed
 - Improve naming due to codemod (#4063)
 - Improve naming due to codemod (#4064)
 - Improve naming due to codemod (#4065)
-- separare the github build into two conditions (#4066)
+- separate the github build into two conditions (#4066)
 - Improve naming due to codemod (#4070)
 - improve naming due to codemod (#4067)
 - improve naming due to codemod (#4071)
 - improve naming due to codemod (#4072)
-- fix nightily build (#4080)
+- fix nightly build (#4080)
 - Change github action workflows name (#4083)
 - Resolve Packaging Issues (#4044)
 - Update __init__.py (#4086)
@@ -474,7 +474,7 @@ Deprecated
 - faster hnsw CPU index training (#3822)
 - Some small improvements. (#3692)
 - First attempt at LSH matching with nbits (#3679)
-- Set verbosoe before train (#3619)
+- Set verbose before train (#3619)
 - Remove duplicate NegativeDistanceComputer instances (#3450)
 - interrupt for NNDescent (#3432)
 - Get rid of redundant instructions in ScalarQuantizer (#3430)
@@ -486,11 +486,11 @@ Deprecated
 - Skip HNSWPQ sdc init with new io flag (#3250)
 
 ### Fixed
-- FIx a bug for a non-simdlib code of ResidualQuantizer (#3868)
+- Fix a bug for a non-simdlib code of ResidualQuantizer (#3868)
 - assign_index should default to null (#3855)
-- Fix an incorrectly counted the number of computed distances for HNSW (#3840)
+- Fix incorrectly counted the number of computed distances for HNSW (#3840)
 - Add error for overflowing nbits during PQ construction (#3833)
-- Fix radius search with HSNW and IP (#3698)
+- Fix radius search with HNSW and IP (#3698)
 - fix algorithm of spreading vectors over shards (#3374)
 - Fix IndexBinary.assign Python method (#3384)
 - Few fixes in bench_fw to enable IndexFromCodec (#3383)
@@ -558,7 +558,7 @@ Deprecated
 - Improved ResidualQuantizer vector encoding (pooling memory allocations, avoid r/w to a temporary buffer)
 
 ### Fixed
-- HSNW bug fixed which improves the recall rate! Special thanks to zh Wang @hhy3 for this.
+- HNSW bug fixed which improves the recall rate! Special thanks to zh Wang @hhy3 for this.
 - Faiss GPU IVF large query batch fix
 - Faiss + Torch fixes, re-enable k = 2048
 - Fix the number of distance computations to match max_codes parameter
@@ -599,7 +599,7 @@ Deprecated
 - Implementation of Local Search Quantization (by @KinglittleQ)
 
 ### Changed
-- The order of xb an xq was different between `faiss.knn` and `faiss.knn_gpu`.
+- The order of xb and xq was different between `faiss.knn` and `faiss.knn_gpu`.
 Also the metric argument was called distance_type.
 - The typed vectors (LongVector, LongLongVector, etc.) of the SWIG interface have
 been deprecated. They have been replaced with Int32Vector, Int64Vector, etc. (by h-vetinari)
@@ -730,7 +730,7 @@ propagated.
 - Support for IMI2x16 (4B virtual centroids).
 - Support for k = 2048 search on GPU (instead of 1024).
 - Support for renaming an ondisk invertedlists.
-- Support for nterrupting computations with interrupt signal (ctrl-C) in python.
+- Support for interrupting computations with interrupt signal (ctrl-C) in python.
 - Simplified build system (with --with-cuda/--with-cuda-arch options).
 
 ### Changed
diff --git a/benchs/bench_all_ivf/parse_bench_all_ivf.py b/benchs/bench_all_ivf/parse_bench_all_ivf.py
index cb22f143e..8a5477f73 100644
--- a/benchs/bench_all_ivf/parse_bench_all_ivf.py
+++ b/benchs/bench_all_ivf/parse_bench_all_ivf.py
@@ -136,7 +136,7 @@ def collect_results_for(db='deep1M', prefix="autotune."):
             print("FAIL %s" % e)
             res = np.zeros((2, 0))
         except Exception as e:
-            print("PARSE ERROR " + e)
+            print("PARSE ERROR " + str(e))
             res = np.zeros((2, 0))
         else:
             print(len(res), "results")
diff --git a/benchs/bench_cppcontrib_sa_decode.cpp b/benchs/bench_cppcontrib_sa_decode.cpp
index 42f98abd7..f47ef6cbd 100644
--- a/benchs/bench_cppcontrib_sa_decode.cpp
+++ b/benchs/bench_cppcontrib_sa_decode.cpp
@@ -221,9 +221,9 @@ static void verifyIndex2LevelDecoder(
 
     // generate a random order of points
     std::uniform_int_distribution<uint64_t> un(0, n - 1);
-    std::vector<uint64_t> pointIncidesToDecode(nIterations * n, 0);
+    std::vector<uint64_t> pointIndicesToDecode(nIterations * n, 0);
     for (uint64_t i = 0; i < nIterations * n; i++) {
-        pointIncidesToDecode[i] = un(rng);
+        pointIndicesToDecode[i] = un(rng);
     }
 
     {
@@ -234,7 +234,7 @@ static void verifyIndex2LevelDecoder(
         StopWatch swFaiss;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 index->sa_decode(
                         1,
                         encodedData.data() + pointIdx * codeSize,
@@ -247,7 +247,7 @@ static void verifyIndex2LevelDecoder(
         StopWatch swKernel;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 T::store(
                         pqCoarseCentroidsQ,
                         pqFineCentroidsQ,
@@ -289,7 +289,7 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 index->sa_decode(
                         1,
@@ -307,7 +307,7 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -331,10 +331,10 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -360,10 +360,10 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -391,13 +391,13 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -425,13 +425,13 @@ static void verifyIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -532,9 +532,9 @@ static void verifyMinMaxIndex2LevelDecoder(
 
     // generate a random order of points
     std::uniform_int_distribution<uint64_t> un(0, n - 1);
-    std::vector<uint64_t> pointIncidesToDecode(nIterations * n, 0);
+    std::vector<uint64_t> pointIndicesToDecode(nIterations * n, 0);
     for (uint64_t i = 0; i < nIterations * n; i++) {
-        pointIncidesToDecode[i] = un(rng);
+        pointIndicesToDecode[i] = un(rng);
     }
 
     {
@@ -545,7 +545,7 @@ static void verifyMinMaxIndex2LevelDecoder(
         StopWatch swFaiss;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 index->sa_decode(
                         1,
                         encodedData.data() + pointIdx * codeSize,
@@ -558,7 +558,7 @@ static void verifyMinMaxIndex2LevelDecoder(
         StopWatch swKernel;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 T::store(
                         pqCoarseCentroidsQ,
                         pqFineCentroidsQ,
@@ -601,7 +601,7 @@ static void verifyMinMaxIndex2LevelDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 index->sa_decode(
                         1,
@@ -620,7 +620,7 @@ static void verifyMinMaxIndex2LevelDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -649,10 +649,10 @@ static void verifyMinMaxIndex2LevelDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -683,10 +683,10 @@ static void verifyMinMaxIndex2LevelDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -719,13 +719,13 @@ static void verifyMinMaxIndex2LevelDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -758,13 +758,13 @@ static void verifyMinMaxIndex2LevelDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqCoarseCentroidsQ,
@@ -859,9 +859,9 @@ static void verifyIndexPQDecoder(
 
     // generate a random order of points
     std::uniform_int_distribution<uint64_t> un(0, n - 1);
-    std::vector<uint64_t> pointIncidesToDecode(nIterations * n, 0);
+    std::vector<uint64_t> pointIndicesToDecode(nIterations * n, 0);
     for (uint64_t i = 0; i < nIterations * n; i++) {
-        pointIncidesToDecode[i] = un(rng);
+        pointIndicesToDecode[i] = un(rng);
     }
 
     {
@@ -872,7 +872,7 @@ static void verifyIndexPQDecoder(
         StopWatch swFaiss;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 index->sa_decode(
                         1,
                         encodedData.data() + pointIdx * codeSize,
@@ -885,7 +885,7 @@ static void verifyIndexPQDecoder(
         StopWatch swKernel;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 T::store(
                         pqFineCentroidsQ,
                         encodedData.data() + pointIdx * codeSize,
@@ -927,7 +927,7 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 index->sa_decode(
                         1,
@@ -945,7 +945,7 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 T::accum(
                         pqFineCentroidsQ,
@@ -968,10 +968,10 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqFineCentroidsQ,
@@ -996,10 +996,10 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1025,13 +1025,13 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1058,13 +1058,13 @@ static void verifyIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1157,9 +1157,9 @@ static void verifyMinMaxIndexPQDecoder(
 
     // generate a random order of points
     std::uniform_int_distribution<uint64_t> un(0, n - 1);
-    std::vector<uint64_t> pointIncidesToDecode(nIterations * n, 0);
+    std::vector<uint64_t> pointIndicesToDecode(nIterations * n, 0);
     for (uint64_t i = 0; i < nIterations * n; i++) {
-        pointIncidesToDecode[i] = un(rng);
+        pointIndicesToDecode[i] = un(rng);
     }
 
     {
@@ -1170,7 +1170,7 @@ static void verifyMinMaxIndexPQDecoder(
         StopWatch swFaiss;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 index->sa_decode(
                         1,
                         encodedData.data() + pointIdx * codeSize,
@@ -1183,7 +1183,7 @@ static void verifyMinMaxIndexPQDecoder(
         StopWatch swKernel;
         for (uint64_t iter = 0; iter < nIterations; iter++) {
             for (uint64_t i = 0; i < n; i++) {
-                const auto pointIdx = pointIncidesToDecode[i + iter * n];
+                const auto pointIdx = pointIndicesToDecode[i + iter * n];
                 T::store(
                         pqFineCentroidsQ,
                         encodedData.data() + pointIdx * codeSize,
@@ -1225,7 +1225,7 @@ static void verifyMinMaxIndexPQDecoder(
         for (uint64_t i = 0; i < n; i++) {
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 index->sa_decode(
                         1,
@@ -1244,7 +1244,7 @@ static void verifyMinMaxIndexPQDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter++) {
                 const auto pointIdx =
-                        pointIncidesToDecode[i * nIterations + iter];
+                        pointIndicesToDecode[i * nIterations + iter];
                 const auto weight = weights[i * nIterations + iter];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1272,10 +1272,10 @@ static void verifyMinMaxIndexPQDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1305,10 +1305,10 @@ static void verifyMinMaxIndexPQDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 2) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1339,13 +1339,13 @@ static void verifyMinMaxIndexPQDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqFineCentroidsQ,
@@ -1377,13 +1377,13 @@ static void verifyMinMaxIndexPQDecoder(
             float outputAccumMin = 0;
             for (uint64_t iter = 0; iter < nIterations; iter += 3) {
                 const auto pointIdx0 =
-                        pointIncidesToDecode[i * nIterations + iter + 0];
+                        pointIndicesToDecode[i * nIterations + iter + 0];
                 const auto weight0 = weights[i * nIterations + iter + 0];
                 const auto pointIdx1 =
-                        pointIncidesToDecode[i * nIterations + iter + 1];
+                        pointIndicesToDecode[i * nIterations + iter + 1];
                 const auto weight1 = weights[i * nIterations + iter + 1];
                 const auto pointIdx2 =
-                        pointIncidesToDecode[i * nIterations + iter + 2];
+                        pointIndicesToDecode[i * nIterations + iter + 2];
                 const auto weight2 = weights[i * nIterations + iter + 2];
                 T::accum(
                         pqFineCentroidsQ,
diff --git a/benchs/bench_fw/descriptors.py b/benchs/bench_fw/descriptors.py
index 666ad1d3a..a344205ce 100644
--- a/benchs/bench_fw/descriptors.py
+++ b/benchs/bench_fw/descriptors.py
@@ -326,7 +326,7 @@ class IndexDescriptor(IndexBaseDescriptor):
         self.flat_desc_name = self.codec_desc.flat_name() + self.database_desc.get_filename(prefix=IndexDescriptor.FILENAME_PREFIX)
         return self.flat_desc_name
 
-    # alias is used to refer when index is uploaded to blobstore and refered again
+    # alias is used to refer when index is uploaded to blobstore and referred again
     def alias(self, benchmark_io: BenchmarkIO):
         if hasattr(benchmark_io, "bucket"):
             return IndexDescriptor(desc_name=self.get_name(), bucket=benchmark_io.bucket, path=self.get_path(benchmark_io), d=self.d, metric=self.metric)
diff --git a/benchs/bench_fw/index.py b/benchs/bench_fw/index.py
index b1252ad1b..b0d12c246 100644
--- a/benchs/bench_fw/index.py
+++ b/benchs/bench_fw/index.py
@@ -558,7 +558,7 @@ class IndexBase:
             "construction_params": self.get_construction_params(),
             "search_params": search_parameters,
         }
-        logger.info("range_seach: end")
+        logger.info("range_search: end")
         return lims, D, I, R, P, None
 
 
diff --git a/benchs/bench_gpu_1bn.py b/benchs/bench_gpu_1bn.py
index 04f6fa927..fc17e9de7 100644
--- a/benchs/bench_gpu_1bn.py
+++ b/benchs/bench_gpu_1bn.py
@@ -166,7 +166,7 @@ def rate_limited_imap(f, l):
 
 
 class IdentPreproc:
-    """a pre-processor is either a faiss.VectorTransform or an IndentPreproc"""
+    """a pre-processor is either a faiss.VectorTransform or an IdentPreproc"""
 
     def __init__(self, d):
         self.d_in = self.d_out = d
@@ -229,7 +229,7 @@ elif dbname == 'Deep1B':
     xb = mmap_fvecs('deep1b/base.fvecs')
     xq = mmap_fvecs('deep1b/deep1B_queries.fvecs')
     xt = mmap_fvecs('deep1b/learn.fvecs')
-    # deep1B's train is is outrageously big
+    # deep1B's train is outrageously big
     xt = xt[:10 * 1000 * 1000]
     gt_I = ivecs_read('deep1b/deep1B_groundtruth.ivecs')
 
@@ -740,11 +740,11 @@ def eval_dataset(index, preproc):
                 print("1-R@%d: %.4f" % (rank, nok / float(nq)), end=' ')
             print()
         if I_fname:
-            I_fname_i = I_fname % I
+            I_fname_i = I_fname % nprobe
             print("storing", I_fname_i)
             np.save(I, I_fname_i)
         if D_fname:
-            D_fname_i = I_fname % I
+            D_fname_i = D_fname % nprobe
             print("storing", D_fname_i)
             np.save(D, D_fname_i)
 
diff --git a/benchs/bench_hybrid_cpu_gpu.py b/benchs/bench_hybrid_cpu_gpu.py
index 7fe3e2546..f6df7b8c4 100644
--- a/benchs/bench_hybrid_cpu_gpu.py
+++ b/benchs/bench_hybrid_cpu_gpu.py
@@ -282,7 +282,7 @@ def main():
 
     group = parser.add_argument_group('dataset options')
     aa('--nq', type=int, default=int(10e5),
-       help="nb queries (queries will be duplicated if below that number")
+       help="nb queries (queries will be duplicated if below that number)")
     aa('--db', default='bigann10M', help='dataset')
 
     group = parser.add_argument_group('index options')
@@ -311,7 +311,7 @@ def main():
         help="how to search"
     )
     aa('--ivf_quant_nlist', type=int, default=1024,
-       help="nb of invlists for IVF quantizer")
+       help="nb of inverted lists for IVF quantizer")
     aa('--batch_size', type=int, default=-1,
        help="batch size for tiled CPU / GPU computation (-1= no tiling)")
     aa('--n_autotune', type=int, default=300,
@@ -540,7 +540,7 @@ def main():
     op.all_experiments = []
     op.platform = {
         "loadavg": open("/proc/loadavg", "r").readlines(),
-        "procesor": [l for l in open("/proc/cpuinfo") if "model name" in l][0],
+        "processor": [l for l in open("/proc/cpuinfo") if "model name" in l][0],
         "GPU": list(os.popen("nvidia-smi", "r")),
         "mem": open("/proc/meminfo", "r").readlines(),
         "pid": os.getpid()
diff --git a/benchs/bench_ivf_flat_panorama.py b/benchs/bench_ivf_flat_panorama.py
index a7fab3c03..85cf84059 100644
--- a/benchs/bench_ivf_flat_panorama.py
+++ b/benchs/bench_ivf_flat_panorama.py
@@ -93,6 +93,7 @@ eval_and_plot(f"IVF{nlist},Flat")
 eval_and_plot(f"PCA{d},IVF{nlist},FlatPanorama{nlevels}")
 
 plt.title("IVF Flat Indexes on GIST1M")
+plt.title("Indices on GIST1M")
 plt.xlabel(f"Recall@{k}")
 plt.ylabel("QPS")
 plt.yscale("log")
diff --git a/benchs/bench_partition.py b/benchs/bench_partition.py
index 5a26584bb..04609e7de 100644
--- a/benchs/bench_partition.py
+++ b/benchs/bench_partition.py
@@ -59,7 +59,7 @@ def do_partition(n, qin, maxval=65536, seed=123, id_type='int64'):
 
     print(
         f"times {times.mean():.3f} µs (± {times.std():.4f} µs) nerr={nerr} "
-        f"bissect {stats.bissect_cycles / 1e6:.3f} Mcy "
+        f"bisect {stats.bissect_cycles / 1e6:.3f} Mcy "
         f"compress {stats.compress_cycles / 1e6:.3f} Mcy"
     )
 
diff --git a/benchs/bench_polysemous_1bn.py b/benchs/bench_polysemous_1bn.py
index 8cbfe0e0d..a73722e09 100644
--- a/benchs/bench_polysemous_1bn.py
+++ b/benchs/bench_polysemous_1bn.py
@@ -69,7 +69,7 @@ elif dbname == 'Deep1B':
     xb = mmap_fvecs('deep1b/base.fvecs')
     xq = mmap_fvecs('deep1b/deep1B_queries.fvecs')
     xt = mmap_fvecs('deep1b/learn.fvecs')
-    # deep1B's train is is outrageously big
+    # deep1B's train is outrageously big
     xt = xt[:10 * 1000 * 1000]
     gt = ivecs_read('deep1b/deep1B_groundtruth.ivecs')
 
diff --git a/benchs/bench_pq_tables.py b/benchs/bench_pq_tables.py
index b22a68573..b7ea31cf1 100644
--- a/benchs/bench_pq_tables.py
+++ b/benchs/bench_pq_tables.py
@@ -73,5 +73,5 @@ for have_threads in False, True:
                     res = run_bench(M * dsub, dsub, nbit, metric)
                     allres.append(res)
         allres = np.array(allres)
-        print("formated result:")
+        print("formatted result:")
         print(format_tab(allres))
diff --git a/benchs/distributed_ondisk/combined_index.py b/benchs/distributed_ondisk/combined_index.py
index a9449f6e0..45f3618d1 100755
--- a/benchs/distributed_ondisk/combined_index.py
+++ b/benchs/distributed_ondisk/combined_index.py
@@ -136,7 +136,6 @@ class CombinedIndex:
         for idx in self.indexes:
             il = faiss.downcast_InvertedLists(
                 faiss.extract_index_ivf(idx).invlists)
-            il.prefetch_nthread
             il.prefetch_nthread = nt
 
     def set_omp_num_threads(self, nt):
diff --git a/benchs/distributed_ondisk/run_on_cluster.bash b/benchs/distributed_ondisk/run_on_cluster.bash
index 886fdcbba..c203d3645 100755
--- a/benchs/distributed_ondisk/run_on_cluster.bash
+++ b/benchs/distributed_ondisk/run_on_cluster.bash
@@ -42,11 +42,11 @@ elif [ $todo == test_kmeans_1 ]; then
            --k $k --gpu -1
 
 elif [ $todo == test_kmeans_2 ]; then
-    # distrbuted run, with one local server per GPU
+    # distributed run, with one local server per GPU
     ngpu=$( echo /dev/nvidia? | wc -w )
     baseport=12012
 
-    # kill background porcesses on output of this script
+    # kill background processes on output of this script
     trap 'kill -HUP 0' 0
 
     hostports=''
diff --git a/demos/demo_auto_tune.py b/demos/demo_auto_tune.py
index 7e98a0116..73ddc825f 100755
--- a/demos/demo_auto_tune.py
+++ b/demos/demo_auto_tune.py
@@ -101,7 +101,7 @@ use_gpu = False
 
 
 if use_gpu:
-    # if this fails, it means that the GPU version was not comp
+    # if this fails, it means that the GPU version was not compiled
     assert faiss.StandardGpuResources, \
         "Faiss was not compiled with GPU support, or loading _swigfaiss_gpu.so failed"
     res = faiss.StandardGpuResources()
diff --git a/demos/demo_distributed_kmeans_torch.py b/demos/demo_distributed_kmeans_torch.py
index a0d78ad81..c3f9780af 100644
--- a/demos/demo_distributed_kmeans_torch.py
+++ b/demos/demo_distributed_kmeans_torch.py
@@ -113,7 +113,7 @@ class DatasetAssignDistributedGPU(clustering.DatasetAssign):
         torch.distributed.reduce(sum_per_centroid, 0)
 
         if rank == 0:
-            # gather deos not support tensors of different sizes
+            # gather does not support tensors of different sizes
             # should be implemented with point-to-point communication
             assert np.all(self.sizes == self.sizes[0])
             device = self.device
diff --git a/demos/demo_imi_flat.cpp b/demos/demo_imi_flat.cpp
index a7f70bca1..ccf9072ee 100644
--- a/demos/demo_imi_flat.cpp
+++ b/demos/demo_imi_flat.cpp
@@ -63,14 +63,14 @@ int main() {
            ncentroids,
            nb);
 
-    // the coarse quantizer should not be dealloced before the index
+    // the coarse quantizer should not be deallocated before the index
     // 4 = nb of bytes per code (d must be a multiple of this)
     // 8 = nb of bits per sub-code (almost always 8)
     faiss::MetricType metric = faiss::METRIC_L2; // can be METRIC_INNER_PRODUCT
     faiss::IndexIVFFlat index(&coarse_quantizer, d, ncentroids, metric);
     index.quantizer_trains_alone = true;
 
-    // define the number of probes. 2048 is for high-dim, overkilled in practice
+    // define the number of probes. 2048 is for high-dim, overkill in practice
     // Use 4-1024 depending on the trade-off speed accuracy that you want
     index.nprobe = 2048;
 
diff --git a/demos/demo_imi_pq.cpp b/demos/demo_imi_pq.cpp
index 1e6387312..96019f08d 100644
--- a/demos/demo_imi_pq.cpp
+++ b/demos/demo_imi_pq.cpp
@@ -74,7 +74,7 @@ int main() {
            ncentroids,
            nb);
 
-    // the coarse quantizer should not be dealloced before the index
+    // the coarse quantizer should not be deallocated before the index
     // 4 = nb of bytes per code (d must be a multiple of this)
     // 8 = nb of bits per sub-code (almost always 8)
     faiss::IndexIVFPQ index(
diff --git a/demos/demo_ivfpq_indexing.cpp b/demos/demo_ivfpq_indexing.cpp
index aa84542cf..bf455dc54 100644
--- a/demos/demo_ivfpq_indexing.cpp
+++ b/demos/demo_ivfpq_indexing.cpp
@@ -41,7 +41,7 @@ int main() {
     // a reasonable number of centroids to index nb vectors
     int ncentroids = int(4 * sqrt(nb));
 
-    // the coarse quantizer should not be dealloced before the index
+    // the coarse quantizer should not be deallocated before the index
     // 4 = nb of bytes per code (d must be a multiple of this)
     // 8 = nb of bits per sub-code (almost always 8)
     faiss::IndexIVFPQ index(&coarse_quantizer, d, ncentroids, 4, 8);
diff --git a/demos/demo_residual_quantizer.cpp b/demos/demo_residual_quantizer.cpp
index 508838143..cacc53783 100644
--- a/demos/demo_residual_quantizer.cpp
+++ b/demos/demo_residual_quantizer.cpp
@@ -76,7 +76,7 @@ int main() {
 
     faiss::ResidualQuantizer rq(
             d, 7, 6, faiss::AdditiveQuantizer::ST_norm_qint8);
-    // do cheap an inaccurate training
+    // do cheap and inaccurate training
     rq.cp.niter = 5;
     rq.max_beam_size = 5;
     rq.train_type = 0;
diff --git a/demos/demo_sift1M.cpp b/demos/demo_sift1M.cpp
index 99a2e9c5b..f9a0fb699 100644
--- a/demos/demo_sift1M.cpp
+++ b/demos/demo_sift1M.cpp
@@ -23,7 +23,7 @@
  *
  *   http://corpus-texmex.irisa.fr/
  *
- * and unzip it to the sudirectory sift1M.
+ * and unzip it to the subdirectory sift1M.
  **/
 
 /*****************************************************
diff --git a/demos/offline_ivf/README.md b/demos/offline_ivf/README.md
index df848ba0a..5f8e926a2 100644
--- a/demos/offline_ivf/README.md
+++ b/demos/offline_ivf/README.md
@@ -48,5 +48,4 @@ b. A new dataset needs to be prepared (step 1) before passing it to the query ve
 
 6. We can always run the consistency-check for sanity checks!
 
-`python run.py  --command consistency_check--config config_ssnpp.yaml --xb ssnpp_1B`
-
+`python run.py  --command consistency_check --config config_ssnpp.yaml --xb ssnpp_1B`
diff --git a/demos/offline_ivf/offline_ivf.py b/demos/offline_ivf/offline_ivf.py
index 8fe7d6b39..75430d65c 100644
--- a/demos/offline_ivf/offline_ivf.py
+++ b/demos/offline_ivf/offline_ivf.py
@@ -284,7 +284,7 @@ class OfflineIVF:
                         logging.info(jj)
                         assert (
                             jj <= self.shard_size
-                        ), f"jj {jj} and shard_zide {self.shard_size}"
+                        ), f"jj {jj} and shard_size {self.shard_size}"
                         if jj == self.shard_size:
                             break
                 logging.info(f"writing {sfn}...")
diff --git a/demos/rocksdb_ivf/README.md b/demos/rocksdb_ivf/README.md
index cf29ee2fd..fca65fcd2 100644
--- a/demos/rocksdb_ivf/README.md
+++ b/demos/rocksdb_ivf/README.md
@@ -19,5 +19,5 @@ make -C build -j$(nproc)
 
 ```
 cd ~/faiss/demos/rocksdb_ivf/build
-./rocksdb_ivf test_db
+./demo_rocksdb_ivf test_db
 ```
diff --git a/faiss/gpu/utils/blockselect/BlockSelectFloatF512.cu b/faiss/gpu/utils/blockselect/BlockSelectFloatF512.cu
index c8060af2f..b0a324427 100644
--- a/faiss/gpu/utils/blockselect/BlockSelectFloatF512.cu
+++ b/faiss/gpu/utils/blockselect/BlockSelectFloatF512.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 BLOCK_SELECT_IMPL(float, false, 512, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/gpu/utils/blockselect/BlockSelectFloatT1024.cu b/faiss/gpu/utils/blockselect/BlockSelectFloatT1024.cu
index 3d0fb6589..14459f4b2 100644
--- a/faiss/gpu/utils/blockselect/BlockSelectFloatT1024.cu
+++ b/faiss/gpu/utils/blockselect/BlockSelectFloatT1024.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 BLOCK_SELECT_IMPL(float, true, 1024, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/gpu/utils/blockselect/BlockSelectFloatT512.cu b/faiss/gpu/utils/blockselect/BlockSelectFloatT512.cu
index 485d13c26..92bc98d32 100644
--- a/faiss/gpu/utils/blockselect/BlockSelectFloatT512.cu
+++ b/faiss/gpu/utils/blockselect/BlockSelectFloatT512.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 BLOCK_SELECT_IMPL(float, true, 512, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/gpu/utils/warpselect/WarpSelectFloatF512.cu b/faiss/gpu/utils/warpselect/WarpSelectFloatF512.cu
index c35dce5b8..19dbc514c 100644
--- a/faiss/gpu/utils/warpselect/WarpSelectFloatF512.cu
+++ b/faiss/gpu/utils/warpselect/WarpSelectFloatF512.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 WARP_SELECT_IMPL(float, false, 512, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/gpu/utils/warpselect/WarpSelectFloatT1024.cu b/faiss/gpu/utils/warpselect/WarpSelectFloatT1024.cu
index f803b1b49..46f2a36ab 100644
--- a/faiss/gpu/utils/warpselect/WarpSelectFloatT1024.cu
+++ b/faiss/gpu/utils/warpselect/WarpSelectFloatT1024.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 WARP_SELECT_IMPL(float, true, 1024, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/gpu/utils/warpselect/WarpSelectFloatT512.cu b/faiss/gpu/utils/warpselect/WarpSelectFloatT512.cu
index 10782f6f1..b436b2d92 100644
--- a/faiss/gpu/utils/warpselect/WarpSelectFloatT512.cu
+++ b/faiss/gpu/utils/warpselect/WarpSelectFloatT512.cu
@@ -12,5 +12,5 @@ namespace gpu {
 
 WARP_SELECT_IMPL(float, true, 512, 8);
 
-}
+} // namespace gpu
 } // namespace faiss
diff --git a/faiss/impl/IDSelector.h b/faiss/impl/IDSelector.h
index 5c24f1e69..be7391520 100644
--- a/faiss/impl/IDSelector.h
+++ b/faiss/impl/IDSelector.h
@@ -131,7 +131,7 @@ struct IDSelectorAll : IDSelector {
     virtual ~IDSelectorAll() {}
 };
 
-/// does an AND operation on the the two given IDSelector's is_membership
+/// does an AND operation on the two given IDSelector's is_membership
 /// results.
 struct IDSelectorAnd : IDSelector {
     const IDSelector* lhs;
@@ -144,7 +144,7 @@ struct IDSelectorAnd : IDSelector {
     virtual ~IDSelectorAnd() {}
 };
 
-/// does an OR operation on the the two given IDSelector's is_membership
+/// does an OR operation on the two given IDSelector's is_membership
 /// results.
 struct IDSelectorOr : IDSelector {
     const IDSelector* lhs;
@@ -157,7 +157,7 @@ struct IDSelectorOr : IDSelector {
     virtual ~IDSelectorOr() {}
 };
 
-/// does an XOR operation on the the two given IDSelector's is_membership
+/// does an XOR operation on the two given IDSelector's is_membership
 /// results.
 struct IDSelectorXOr : IDSelector {
     const IDSelector* lhs;
diff --git a/faiss/invlists/BlockInvertedLists.h b/faiss/invlists/BlockInvertedLists.h
index 7f608a87a..fcbe06b92 100644
--- a/faiss/invlists/BlockInvertedLists.h
+++ b/faiss/invlists/BlockInvertedLists.h
@@ -20,7 +20,7 @@ struct IDSelector;
 /** Inverted Lists that are organized by blocks.
  *
  * Different from the regular inverted lists, the codes are organized by blocks
- * of size block_size bytes that reprsent a set of n_per_block. Therefore, code
+ * of size block_size bytes that represent a set of n_per_block. Therefore, code
  * allocations are always rounded up to block_size bytes. The codes are also
  * aligned on 32-byte boundaries for use with SIMD.
  *
diff --git a/faiss/invlists/DirectMap.cpp b/faiss/invlists/DirectMap.cpp
index 50ff71177..a83a0e5e9 100644
--- a/faiss/invlists/DirectMap.cpp
+++ b/faiss/invlists/DirectMap.cpp
@@ -53,7 +53,7 @@ void DirectMap::set_type(
             for (long ofs = 0; ofs < list_size; ofs++) {
                 FAISS_THROW_IF_NOT_MSG(
                         0 <= idlist[ofs] && idlist[ofs] < ntotal,
-                        "direct map supported only for seuquential ids");
+                        "direct map supported only for sequential ids");
                 array[idlist[ofs]] = lo_build(key, ofs);
             }
         } else if (new_type == Hashtable) {
diff --git a/faiss/invlists/InvertedLists.cpp b/faiss/invlists/InvertedLists.cpp
index e079b6c42..448b96973 100644
--- a/faiss/invlists/InvertedLists.cpp
+++ b/faiss/invlists/InvertedLists.cpp
@@ -229,7 +229,7 @@ bool InvertedLists::is_empty(size_t list_no, void* inverted_list_context)
     }
 }
 
-// implemnent iterator on top of get_codes / get_ids
+// implement iterator on top of get_codes / get_ids
 namespace {
 
 struct CodeArrayIterator : InvertedListsIterator {
diff --git a/faiss/invlists/OnDiskInvertedLists.cpp b/faiss/invlists/OnDiskInvertedLists.cpp
index cc37fd1e2..a53668a6d 100644
--- a/faiss/invlists/OnDiskInvertedLists.cpp
+++ b/faiss/invlists/OnDiskInvertedLists.cpp
@@ -372,7 +372,7 @@ OnDiskInvertedLists::~OnDiskInvertedLists() {
     if (ptr != nullptr) {
         int err = munmap(ptr, totsize);
         if (err != 0) {
-            fprintf(stderr, "mumap error: %s", strerror(errno));
+            fprintf(stderr, "munmap error: %s", strerror(errno));
         }
     }
     delete locks;
diff --git a/faiss/invlists/OnDiskInvertedLists.h b/faiss/invlists/OnDiskInvertedLists.h
index 52953f9c0..b809d4c79 100644
--- a/faiss/invlists/OnDiskInvertedLists.h
+++ b/faiss/invlists/OnDiskInvertedLists.h
@@ -121,7 +121,7 @@ struct OnDiskInvertedLists : InvertedLists {
 
     LockLevels* locks;
 
-    // encapsulates the threads that are busy prefeteching
+    // encapsulates the threads that are busy prefetching
     struct OngoingPrefetch;
     OngoingPrefetch* pf;
     int prefetch_nthread;
diff --git a/tutorial/cpp/7-PQFastScan.cpp b/tutorial/cpp/7-PQFastScan.cpp
index 3e0894890..817993c6b 100644
--- a/tutorial/cpp/7-PQFastScan.cpp
+++ b/tutorial/cpp/7-PQFastScan.cpp
@@ -72,4 +72,4 @@ int main() {
     delete[] xq;
 
     return 0;
-} // namespace facebook::detail
+}