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C++ 測試 (代理技能)

僅在編寫/更新/修復 C++ 測試、配置 GoogleTest/CTest、診斷失敗或不穩定測試,或添加覆蓋率/清理器時使用。

C++ 測試 (代理技能) 是什麼?

這項代理技能針對現代 C++(C++17/20)專案,提供以 GoogleTest/GoogleMock 搭配 CMake/CTest 為核心的測試工作流程。它支援從單元測試、整合測試、模擬物件到覆蓋率報告與記憶體/執行緒清理器的完整測試生命週期。技能文件內含完整的 TDD 循環指南(紅-綠-重構)、豐富的程式碼範例(測試案例、測試夾具、互動模擬),以及可直接套用的 CMake 配置範本,讓開發者能快速建立穩固的測試基礎。此外,針對常見的測試痛點(例如不穩定測試的因應對策、隱藏全域狀態的清理、避免過度模擬)也提供具體的最佳實踐與常見陷阱說明,有助於提升測試的可維護性與可靠性。此技能適用於 Claude Code、Cursor、Codex 等支援代理模式的開發工具,能有效引導代理在開發流程中自動產生或修正測試程式碼。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/ECC/tree/main/skills/cpp-testing

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說明文件

C++ 測試 (代理技能) 是做什麼的?

針對代理的測試工作流程,適用於使用 GoogleTest/GoogleMock 搭配 CMake/CTest 的現代 C++(C++17/20)。

使用時機

  • 編寫新的 C++ 測試或修復現有的測試
  • 為 C++ 元件設計單元/整合測試覆蓋率
  • 增加測試覆蓋率、CI 閘道或回歸保護
  • 配置 CMake/CTest 工作流程以確保一致的執行
  • 調查測試失敗或不穩定行為
  • 啟用清理器進行記憶體/競爭診斷

何時不應使用

  • 實作不包含測試變更的新產品功能
  • 與測試覆蓋率或失敗無關的大規模重構
  • 效能調校但無測試回歸可驗證
  • 非 C++ 專案或非測試任務

核心概念

  • TDD 循環:紅(RED)→ 綠(GREEN)→ 重構(REFACTOR)(先寫測試,最小修正,再清理)。
  • 隔離:偏好依賴注入與假物件(fakes),避免使用全域狀態。
  • 測試佈局:tests/unit、tests/integration、tests/testdata。
  • 模擬 vs 假物件:模擬(mock)用於互動驗證,假物件(fake)用於有狀態的行為。
  • CTest 發現:使用 gtest_discover_tests() 實現穩定的測試發現。
  • CI 信號:先執行子集,再以 --output-on-failure 執行完整測試套件。

TDD 工作流程

遵循 紅(RED)→ 綠(GREEN)→ 重構(REFACTOR)循環:

  1. 紅(RED):編寫一個會失敗的測試來捕捉新行為
  2. 綠(GREEN):實作最小的變更使其通過
  3. 重構(REFACTOR):在測試保持綠燈的同時進行清理
// tests/add_test.cpp
#include <gtest/gtest.h>

int Add(int a, int b); // 由生產程式碼提供。

TEST(AddTest, AddsTwoNumbers) { // 紅(RED)
  EXPECT_EQ(Add(2, 3), 5);
}

// src/add.cpp
int Add(int a, int b) { // 綠(GREEN)
  return a + b;
}

// 重構(REFACTOR):測試通過後簡化/重新命名

程式碼範例

基本單元測試 (gtest)

// tests/calculator_test.cpp
#include <gtest/gtest.h>

int Add(int a, int b); // 由生產程式碼提供。

TEST(CalculatorTest, AddsTwoNumbers) {
    EXPECT_EQ(Add(2, 3), 5);
}

測試夾具 (gtest)

// tests/user_store_test.cpp
// 虛擬碼存根:請以專案中的 UserStore/User 類型取代。
#include <gtest/gtest.h>
#include <memory>
#include <optional>
#include <string>

struct User { std::string name; };
class UserStore {
public:
    explicit UserStore(std::string /*path*/) {}
    void Seed(std::initializer_list<User> /*users*/) {}
    std::optional<User> Find(const std::string &/*name*/) { return User{"alice"}; }
};

class UserStoreTest : public ::testing::Test {
protected:
    void SetUp() override {
        store = std::make_unique<UserStore>(":memory:");
        store->Seed({{"alice"}, {"bob"}});
    }

    std::unique_ptr<UserStore> store;
};

TEST_F(UserStoreTest, FindsExistingUser) {
    auto user = store->Find("alice");
    ASSERT_TRUE(user.has_value());
    EXPECT_EQ(user->name, "alice");
}

模擬物件 (gmock)

// tests/notifier_test.cpp
#include <gmock/gmock.h>
#include <gtest/gtest.h>
#include <string>

class Notifier {
public:
    virtual ~Notifier() = default;
    virtual void Send(const std::string &message) = 0;
};

class MockNotifier : public Notifier {
public:
    MOCK_METHOD(void, Send, (const std::string &message), (override));
};

class Service {
public:
    explicit Service(Notifier &notifier) : notifier_(notifier) {}
    void Publish(const std::string &message) { notifier_.Send(message); }

private:
    Notifier &notifier_;
};

TEST(ServiceTest, SendsNotifications) {
    MockNotifier notifier;
    Service service(notifier);

    EXPECT_CALL(notifier, Send("hello")).Times(1);
    service.Publish("hello");
}

CMake/CTest 快速入門

# CMakeLists.txt (摘錄)
cmake_minimum_required(VERSION 3.20)
project(example LANGUAGES CXX)

set(CMAKE_CXX_STANDARD 20)
set(CMAKE_CXX_STANDARD_REQUIRED ON)

include(FetchContent)
# 偏好使用專案鎖定的版本。若使用標籤,請根據專案政策使用固定版本。
set(GTEST_VERSION v1.17.0) # 請依專案政策調整。
FetchContent_Declare(
  googletest
  # Google Test 框架 (官方儲存庫)
  URL https://github.com/google/googletest/archive/refs/tags/${GTEST_VERSION}.zip
)
FetchContent_MakeAvailable(googletest)

add_executable(example_tests
  tests/calculator_test.cpp
  src/calculator.cpp
)
target_link_libraries(example_tests GTest::gtest GTest::gmock GTest::gtest_main)

enable_testing()
include(GoogleTest)
gtest_discover_tests(example_tests)
cmake -S . -B build -DCMAKE_BUILD_TYPE=Debug
cmake --build build -j
ctest --test-dir build --output-on-failure

執行測試

ctest --test-dir build --output-on-failure
ctest --test-dir build -R ClampTest
ctest --test-dir build -R "UserStoreTest.*" --output-on-failure
./build/example_tests --gtest_filter=ClampTest.*
./build/example_tests --gtest_filter=UserStoreTest.FindsExistingUser

除錯失敗

  1. 使用 gtest 過濾器重新執行單一失敗測試。
  2. 在失敗的斷言周圍加入限域的日誌。
  3. 啟用清理器重新執行。
  4. 根因修復後再擴展至完整測試套件。

覆蓋率

偏好使用目標層級的設定,而非全域旗標。

option(ENABLE_COVERAGE "啟用覆蓋率旗標" OFF)

if(ENABLE_COVERAGE)
  if(CMAKE_CXX_COMPILER_ID MATCHES "GNU")
    target_compile_options(example_tests PRIVATE --coverage)
    target_link_options(example_tests PRIVATE --coverage)
  elseif(CMAKE_CXX_COMPILER_ID MATCHES "Clang")
    target_compile_options(example_tests PRIVATE -fprofile-instr-generate -fcoverage-mapping)
    target_link_options(example_tests PRIVATE -fprofile-instr-generate)
  endif()
endif()

GCC + gcov + lcov:

cmake -S . -B build-cov -DENABLE_COVERAGE=ON
cmake --build build-cov -j
ctest --test-dir build-cov
lcov --capture --directory build-cov --output-file coverage.info
lcov --remove coverage.info '/usr/*' --output-file coverage.info
genhtml coverage.info --output-directory coverage

Clang + llvm-cov:

cmake -S . -B build-llvm -DENABLE_COVERAGE=ON -DCMAKE_CXX_COMPILER=clang++
cmake --build build-llvm -j
LLVM_PROFILE_FILE="build-llvm/default.profraw" ctest --test-dir build-llvm
llvm-profdata merge -sparse build-llvm/default.profraw -o build-llvm/default.profdata
llvm-cov report build-llvm/example_tests -instr-profile=build-llvm/default.profdata

清理器

option(ENABLE_ASAN "啟用 AddressSanitizer" OFF)
option(ENABLE_UBSAN "啟用 UndefinedBehaviorSanitizer" OFF)
option(ENABLE_TSAN "啟用 ThreadSanitizer" OFF)

if(ENABLE_ASAN)
  add_compile_options(-fsanitize=address -fno-omit-frame-pointer)
  add_link_options(-fsanitize=address)
endif()
if(ENABLE_UBSAN)
  add_compile_options(-fsanitize=undefined -fno-omit-frame-pointer)
  add_link_options(-fsanitize=undefined)
endif()
if(ENABLE_TSAN)
  add_compile_options(-fsanitize=thread)
  add_link_options(-fsanitize=thread)
endif()

不穩定測試的防護措施

  • 絕不為同步使用 sleep;應使用條件變數或閂鎖(latch)。
  • 確保每個測試的暫存目錄是唯一且總是清理乾淨。
  • 在單元測試中避免真實時間、網路或檔案系統依賴。
  • 為隨機輸入使用確定性種子。

最佳實踐

該做的事

  • 保持測試確定性與隔離性
  • 偏好依賴注入勝於全域變數
  • 使用 ASSERT_* 作為前置條件,EXPECT_* 進行多項檢查
  • 在 CTest 標籤或目錄中區分單元測試 vs 整合測試
  • 在 CI 中執行清理器以偵測記憶體與競爭問題

不該做的事

  • 不要在單元測試中依賴真實時間或網路
  • 當條件變數可用時,不要使用 sleep 作為同步手段
  • 不要過度模擬簡單的值物件
  • 不要對非關鍵日誌使用脆弱的字串匹配

常見陷阱

  • 使用固定的暫存路徑 → 為每個測試產生唯一暫存目錄並清理。
  • 依賴牆上時鐘時間 → 注入時鐘或使用假的時間來源。
  • 不穩定的並發測試 → 使用條件變數/閂鎖搭配有限等待。
  • 隱藏的全域狀態 → 在測試夾具中重設全域狀態或移除全域變數。
  • 過度模擬 → 對有狀態的行為偏好使用假物件,僅對互動進行模擬。
  • 缺少清理器執行 → 在 CI 中加入 ASan/UBSan/TSan 建置。
  • 僅在除錯建置上測量覆蓋率 → 確保覆蓋率目標使用一致的旗標。

選擇性附錄:模糊測試 / 屬性測試

僅在專案已支援 LLVM/libFuzzer 或屬性測試函式庫時使用。

  • libFuzzer:最適合純函數與最少 I/O 的情境。
  • RapidCheck:基於屬性的測試,用於驗證不變量。

最小的 libFuzzer 測試工具(虛擬碼:請取代 ParseConfig):

#include <cstddef>
#include <cstdint>
#include <string>

extern "C" int LLVMFuzzerTestOneInput(const uint8_t *data, size_t size) {
    std::string input(reinterpret_cast<const char *>(data), size);
    // ParseConfig(input); // 專案函式
    return 0;
}

GoogleTest 的替代方案

  • Catch2:僅標頭檔,表達力強匹配器
  • doctest:輕量級,最小編譯開銷

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

相關技能