[RNE Rewrite] chore: add clang-tidy static checks

.github/workflows/clang-tidy.yml

@@ -0,0 +1,49 @@
+name: clang-tidy
+
+on:
+  pull_request:
+    branches:
+      - main
+      - rne-rewrite
+    paths:
+      - 'packages/react-native-executorch/cpp/**'
+      - 'packages/react-native-executorch/.clang-tidy'
+      - 'packages/react-native-executorch/compile_flags.txt'
+      - 'packages/react-native-executorch/scripts/clang-tidy.sh'
+      - '.github/workflows/clang-tidy.yml'
+  workflow_dispatch:
+
+jobs:
+  clang-tidy:
+    runs-on: ubuntu-latest
+    # Dormant until the on-demand header artifact is published (#1283): clang-tidy
+    # must parse the sources, which needs the ExecuTorch/torch headers that are not
+    # committed. Enable by setting the repo variable ENABLE_CLANG_TIDY=true once a
+    # release carrying headers.tar.gz exists for the package version.
+    if: ${{ vars.ENABLE_CLANG_TIDY == 'true' }}
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v6
+
+      - name: Setup
+        uses: ./.github/actions/setup
+
+      - name: Install clang-tidy
+        run: |
+          sudo apt-get update
+          sudo apt-get install -y clang-tidy
+          clang-tidy --version
+
+      - name: Provision ExecuTorch headers
+        # Reuse the on-demand download flow (#1283). clang-tidy only needs headers
+        # (it syntax-checks, no linking), so RNET_HEADERS_ONLY fetches just
+        # headers.tar.gz; RNET_TARGET avoids host platform auto-detection.
+        working-directory: packages/react-native-executorch
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+          RNET_HEADERS_ONLY: '1'
+          RNET_TARGET: android-arm64-v8a
+        run: node scripts/download-libs.js
+
+      - name: Run clang-tidy
+        run: yarn workspace react-native-executorch lint:cpp

CONTRIBUTING.md

@@ -79,6 +79,20 @@ don't conflict. clangd discovers `compile_flags.txt`/`.clangd` automatically fro
 open file's directory. If you produce a `compile_commands.json` from a native build,
 clangd will prefer it — it's gitignored and takes precedence over `compile_flags.txt`.
 
+## clang-tidy
+
+`packages/react-native-executorch/.clang-tidy` adds a conservative, high-signal set of
+static checks (bugprone / performance / clang-analyzer) on top of the same database. The
+clangd extension surfaces these inline; you can also run them from the command line:
+
+```
+yarn workspace react-native-executorch lint:cpp           # all C++ sources
+CLANG_TIDY=$(brew --prefix llvm)/bin/clang-tidy yarn workspace react-native-executorch lint:cpp
+```
+
+It needs the same provisioned headers as clangd. Suppress an intentional, reviewed finding
+with a commented `// NOLINTNEXTLINE(check-name)` rather than loosening the shared config.
+
 # Creating a Pull Request
 
 Before writing any code reach out to us to make sure no one is currently working on it, you can always open an issue first.

packages/react-native-executorch/.clang-tidy

@@ -0,0 +1,74 @@
+# clang-tidy configuration for the react-native-executorch C/C++ sources.
+#
+# A high-signal set focused on correctness/performance bugs and modern C++
+# guidelines (issue #1271). Check groups are enabled one at a time and the
+# findings fixed; it is expected to stay green on our own code.
+#
+# clang-tidy reads the include flags / standard / defines from compile_flags.txt
+# (the same database clangd uses), so it needs the same prerequisites: a provisioned
+# third-party/include and `yarn install`. The clangd extension also surfaces these
+# checks inline in the editor.
+#
+# Excluded checks (incompatible with a native tensor/buffer library that interops
+# with ExecuTorch over raw pointers, or purely opinionated):
+#   pro-bounds-pointer-arithmetic / -avoid-unchecked-container-access /
+#   -constant-array-index — raw buffer pointer math and hot-loop indexing are by design
+#   pro-type-reinterpret-cast — type-erased byte buffers cast to typed pointers
+#   avoid-magic-numbers / easily-swappable-parameters / enum-size — opinionated / noisy
+#   llvm-header-guard — the project uses #pragma once by convention
+#   llvm-prefer-static-over-anonymous-namespace — anonymous namespaces are a valid
+#     idiom here and also hold the helpers' shared types/constants
+#   misc-include-cleaner — ExecuTorch umbrella headers make it misreport includes
+#   misc-multiple-inheritance — the JSI HostObject + enable_shared_from_this pattern
+#   misc-non-private-member-variables-in-classes — HostObjects are deliberate public
+#     data carriers read across extensions
+#   misc-const-correctness — applied once as a cleanup, but too aggressive to gate on
+#     (it flags RAII lock guards as const-able); not enforced going forward
+#   modernize-use-trailing-return-type — the codebase uses traditional return types
+#   modernize-return-braced-init-list — `return {…}` hides the (JSI) return type
+#   readability-identifier-length — short names (i, rt, h, w, …) are idiomatic here
+#   readability-math-missing-parentheses — flags standard array-offset arithmetic
+#   readability-function-cognitive-complexity — the JSI get() dispatchers and the
+#     image/tensor kernels are inherently above the threshold
+#   readability-uppercase-literal-suffix — the codebase uses lowercase (1.0f) consistently
+#   readability-magic-numbers — opinionated (same as cppcoreguidelines-avoid-magic-numbers)
+Checks: >
+  -*,
+  bugprone-*,
+  performance-*,
+  clang-analyzer-*,
+  cppcoreguidelines-*,
+  google-*,
+  llvm-*,
+  misc-*,
+  modernize-*,
+  readability-*,
+  -bugprone-easily-swappable-parameters,
+  -performance-enum-size,
+  -cppcoreguidelines-pro-bounds-pointer-arithmetic,
+  -cppcoreguidelines-pro-bounds-avoid-unchecked-container-access,
+  -cppcoreguidelines-pro-bounds-constant-array-index,
+  -cppcoreguidelines-pro-type-reinterpret-cast,
+  -cppcoreguidelines-avoid-magic-numbers,
+  -llvm-header-guard,
+  -llvm-prefer-static-over-anonymous-namespace,
+  -misc-include-cleaner,
+  -misc-multiple-inheritance,
+  -misc-non-private-member-variables-in-classes,
+  -misc-const-correctness,
+  -modernize-use-trailing-return-type,
+  -modernize-return-braced-init-list,
+  -readability-identifier-length,
+  -readability-math-missing-parentheses,
+  -readability-function-cognitive-complexity,
+  -readability-uppercase-literal-suffix,
+  -readability-magic-numbers
+
+# Restrict analysis to this package's own cpp/ tree. Anchored on the full package
+# path so it can never match an unrelated directory that merely contains "cpp"
+# (e.g. third-party/.../abseil-cpp/, or another package's cpp/). Third-party headers
+# are also -isystem in compile_flags.txt, so clang-tidy does not analyze them anyway.
+HeaderFilterRegex: 'packages/react-native-executorch/cpp/.*\.(h|hpp)$'
+
+# Treat findings as warnings (CI decides failure via --warnings-as-errors).
+WarningsAsErrors: ''

packages/react-native-executorch/cpp/RnExecutorch.cpp

@@ -5,7 +5,7 @@
 #include "extensions/math/install.h"
 #include "extensions/nlp/install.h"
 
-using namespace facebook;
+namespace jsi = facebook::jsi;
 
 namespace rnexecutorch {
 void install(jsi::Runtime &jsiRuntime) {

packages/react-native-executorch/cpp/core/dtype.cpp

@@ -54,6 +54,8 @@ size_t elementSize(DType dtype) {
     switch (dtype) {
     case DType::uint8:
         return 1;
+    // int32 and float32 are both 4 bytes; the identical branches are intentional.
+    // NOLINTNEXTLINE(bugprone-branch-clone)
     case DType::int32:
         return 4;
     case DType::float32:

packages/react-native-executorch/cpp/core/dtype.h

@@ -5,7 +5,7 @@
 #include <string>
 
 namespace rnexecutorch::core::types {
-enum DType {
+enum class DType {
     uint8,
     int32,
     float32

packages/react-native-executorch/cpp/core/model.cpp

@@ -43,7 +43,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
 
             auto methodNames = self->etModule_->method_names();
             if (!methodNames.ok()) {
-                std::string errorMsg = executorch::runtime::to_string(methodNames.error());
+                const std::string errorMsg = executorch::runtime::to_string(methodNames.error());
                 throw jsi::JSError(rt, "getMethodNames: Failed to get method names: " + errorMsg);
             }
 
@@ -82,15 +82,15 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             auto methodName = args[0].asString(rt).utf8(rt);
             auto methodMeta = self->etModule_->method_meta(methodName);
             if (!methodMeta.ok()) {
-                std::string errorMsg = executorch::runtime::to_string(methodMeta.error());
+                const std::string errorMsg = executorch::runtime::to_string(methodMeta.error());
                 throw jsi::JSError(rt, "getMethodMeta: Failed to get method meta: " + errorMsg);
             }
 
             auto inputTagsArray = jsi::Array(rt, methodMeta->num_inputs());
             for (size_t i = 0; i < methodMeta->num_inputs(); ++i) {
                 auto tag = methodMeta->input_tag(i);
                 if (!tag.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(tag.error());
+                    const std::string errorMsg = executorch::runtime::to_string(tag.error());
                     throw jsi::JSError(rt, "getMethodMeta: Failed to get input tag for input " + std::to_string(i) + ": " + errorMsg);
                 }
                 inputTagsArray.setValueAtIndex(rt, i, jsi::String::createFromUtf8(rt, executorch::runtime::tag_to_string(tag.get())));
@@ -100,7 +100,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             for (size_t i = 0; i < methodMeta->num_outputs(); ++i) {
                 auto tag = methodMeta->output_tag(i);
                 if (!tag.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(tag.error());
+                    const std::string errorMsg = executorch::runtime::to_string(tag.error());
                     throw jsi::JSError(rt, "getMethodMeta: Failed to get output tag for output " + std::to_string(i) + ": " + errorMsg);
                 }
                 outputTagsArray.setValueAtIndex(rt, i, jsi::String::createFromUtf8(rt, executorch::runtime::tag_to_string(tag.get())));
@@ -110,7 +110,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             for (size_t i = 0; i < methodMeta->num_backends(); ++i) {
                 auto backendName = methodMeta->get_backend_name(i);
                 if (!backendName.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(backendName.error());
+                    const std::string errorMsg = executorch::runtime::to_string(backendName.error());
                     throw jsi::JSError(rt, "getMethodMeta: Failed to get backend name for backend " + std::to_string(i) + ": " + errorMsg);
                 }
                 usesBackendMap.setProperty(rt, backendName.get(), methodMeta->uses_backend(backendName.get()));
@@ -123,7 +123,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
                 jsTensorMeta.setProperty(rt, "nbytes", static_cast<double>(tensorMeta.nbytes()));
 
                 try {
-                    std::string dtypeStr = rnexecutorch::core::types::toString(rnexecutorch::core::types::fromScalarType(tensorMeta.scalar_type()));
+                    const std::string dtypeStr = rnexecutorch::core::types::toString(rnexecutorch::core::types::fromScalarType(tensorMeta.scalar_type()));
                     jsTensorMeta.setProperty(rt, "dtype", jsi::String::createFromUtf8(rt, dtypeStr));
                 } catch (const std::exception &) {
                     jsTensorMeta.setProperty(rt, "dtype", jsi::String::createFromUtf8(rt, "not supported"));
@@ -142,7 +142,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             for (size_t i = 0; i < methodMeta->num_inputs(); ++i) {
                 auto tensorMeta = methodMeta->input_tensor_meta(i);
                 if (!tensorMeta.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
+                    const std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
                     throw jsi::JSError(rt, "getMethodMeta: Failed to get tensor meta for input " + std::to_string(i) + ": " + errorMsg);
                 }
                 inputTensorMetaArray.setValueAtIndex(rt, i, tensorMetaToJS(rt, tensorMeta.get()));
@@ -152,7 +152,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             for (size_t i = 0; i < methodMeta->num_outputs(); ++i) {
                 auto tensorMeta = methodMeta->output_tensor_meta(i);
                 if (!tensorMeta.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
+                    const std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
                     throw jsi::JSError(rt, "getMethodMeta: Failed to get tensor meta for output " + std::to_string(i) + ": " + errorMsg);
                 }
                 outputTensorMetaArray.setValueAtIndex(rt, i, tensorMetaToJS(rt, tensorMeta.get()));
@@ -207,14 +207,14 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
             auto inputsArray = args[1].asObject(rt).asArray(rt);
 
             if (!methodMeta.ok()) {
-                std::string errorMsg = executorch::runtime::to_string(methodMeta.error());
+                const std::string errorMsg = executorch::runtime::to_string(methodMeta.error());
                 throw jsi::JSError(rt, "execute: Failed to get method meta for '" + methodName + "': " + errorMsg);
             }
 
             if (inputsArray.size(rt) != methodMeta->num_inputs()) {
-                std::string errorMsg = "execute: Incorrect size for inputs: got " +
-                                       std::to_string(inputsArray.size(rt)) +
-                                       ", expected " + std::to_string(methodMeta->num_inputs());
+                const std::string errorMsg = "execute: Incorrect size for inputs: got " +
+                                             std::to_string(inputsArray.size(rt)) +
+                                             ", expected " + std::to_string(methodMeta->num_inputs());
                 throw jsi::JSError(rt, errorMsg);
             }
 
@@ -252,7 +252,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
                 auto val = inputsArray.getValueAtIndex(rt, i);
 
                 if (!tag.ok()) {
-                    std::string errorMsg = executorch::runtime::to_string(tag.error());
+                    const std::string errorMsg = executorch::runtime::to_string(tag.error());
                     throw jsi::JSError(rt, "execute: Failed to get input tag for inputs[" +
                                                std::to_string(i) + "]: " + errorMsg);
                 }
@@ -290,7 +290,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
                     auto tensorMeta = methodMeta->input_tensor_meta(i);
 
                     if (!tensorMeta.ok()) {
-                        std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
+                        const std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
                         throw jsi::JSError(rt, "execute: Failed to get tensor meta for inputs[" +
                                                    std::to_string(i) + "]: " + errorMsg);
                     }
@@ -343,7 +343,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
 #endif
 
             if (!result.ok()) {
-                std::string errorMsg = executorch::runtime::to_string(result.error());
+                const std::string errorMsg = executorch::runtime::to_string(result.error());
                 throw jsi::JSError(rt, "execute: Method '" + methodName + "' execution failed: " + errorMsg +
                                            ". This may be due to missing required backends - use getMethodMeta()" +
                                            " to check required backends and getExecuTorchRegisteredBackends()" +
@@ -392,7 +392,7 @@ jsi::Value ModelHostObject::get(jsi::Runtime &rt, const jsi::PropNameID &name) {
                     auto tensorMeta = methodMeta->output_tensor_meta(index);
 
                     if (!tensorMeta.ok()) {
-                        std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
+                        const std::string errorMsg = executorch::runtime::to_string(tensorMeta.error());
                         throw jsi::JSError(rt, "execute: Failed to get tensor meta for output at index " +
                                                    std::to_string(index) + ": " + errorMsg);
                     }
@@ -467,7 +467,7 @@ std::vector<facebook::jsi::PropNameID> ModelHostObject::getPropertyNames(jsi::Ru
 }
 
 void install_loadModel(jsi::Runtime &rt, jsi::Object &module) {
-    auto name = "loadModel";
+    const auto *name = "loadModel";
     auto fnBody = [](jsi::Runtime &rt, const jsi::Value & /*thisVal*/, const jsi::Value *args, size_t count) -> jsi::Value {
         if (count != 1) {
             throw jsi::JSError(rt, "loadModel: Usage: loadModel(arg0)");
@@ -482,7 +482,7 @@ void install_loadModel(jsi::Runtime &rt, jsi::Object &module) {
 
         auto error = modelInstance->etModule_->load();
         if (!modelInstance->etModule_->is_loaded()) {
-            std::string errorMsg = executorch::runtime::to_string(error);
+            const std::string errorMsg = executorch::runtime::to_string(error);
             throw jsi::JSError(rt, "loadModel: Failed to load model: " + errorMsg);
         }
 

packages/react-native-executorch/cpp/core/model.h

@@ -24,7 +24,7 @@ class ModelHostObject : public facebook::jsi::HostObject, public std::enable_sha
     std::unique_ptr<executorch::extension::Module> etModule_;
     std::mutex mutex_;
 
-    ModelHostObject(const std::string &modelPath);
+    explicit ModelHostObject(const std::string &modelPath);
 
     facebook::jsi::Value get(facebook::jsi::Runtime &rt, const facebook::jsi::PropNameID &name) override;
     std::vector<facebook::jsi::PropNameID> getPropertyNames(facebook::jsi::Runtime &rt) override;