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Performance optimization techniques in C++ function unit testing?

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Release: 2024-04-25 08:03:01
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The performance of C function unit testing can be improved by adopting the following techniques: disabling unnecessary output and reducing the printing information overhead of the test framework. Cache time-consuming operations to avoid repeated calculations. Use a thread pool to execute tests in parallel to improve test speed. Optimized unit tests execute faster and more stably, allowing for efficient testing of complex functions and larger data sets.

C++ 函数单元测试中性能优化技巧?

Performance optimization tips in C function unit testing

When conducting C function unit testing, optimizing test performance is crucial. This not only speeds up testing but also improves the stability of the test suite. Here are a few practical tips to improve unit testing performance:

Disable unnecessary output

Testing frameworks often print a lot of output information, which can significantly slow down testing. Overhead can be reduced by disabling unnecessary output, for example:

// 禁用 Google Test 框架的输出
testing::GTEST_FLAG(output) = testing::GTEST_OUTPUT_DISABLED;
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Cache expensive operations

If unit tests need to repeatedly perform time-consuming operations, consider caching them. This improves performance by avoiding repeated calculations in each test.

// 缓存昂贵的计算结果
std::map<int, int> cache;

int getCachedValue(int key) {
  auto it = cache.find(key);
  if (it != cache.end()) {
    return it->second;
  }

  // 计算并缓存结果
  int value = /* 计算... */;
  cache[key] = value;
  return value;
}
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Use thread pool

Executing tests in parallel with multiple threads can significantly improve the test speed. This can be achieved by using a thread pool, which can manage and coordinate multiple threads, distributing and executing test tasks among the threads.

// 创建线程池
std::thread::hardware_concurrency();

// 在线程池中执行测试
std::vector<std::future<void>> futures;
for (auto& test : tests) {
  futures.emplace_back(std::async(std::launch::async, test));
}

// 等待所有测试完成
for (auto& future : futures) {
  future.get();
}
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Example analysis

Suppose we have a function compute(), which calculates the prime factors of a large integer. We can optimize its unit tests using the following tips:

  • Disable unnecessary output: The test does not need to output any information.
  • Cache expensive operations: Prime factorization is an expensive operation and its results can be cached.
  • Use thread pool: Multiple test cases can be executed in parallel by using the thread pool.

Optimized unit test code might look like this:

#include <gtest/gtest.h>
#include <future>
#include <vector>

using namespace std;

// 禁用输出
testing::GTEST_FLAG(output) = testing::GTEST_OUTPUT_DISABLED;

// 缓存质因数分解结果
map<int, vector<int>> cache;

vector<int> getFactors(int n) {
  auto it = cache.find(n);
  if (it != cache.end()) {
    return it->second;
  }

  // 计算并缓存质因数
  vector<int> factors;
  for (int i = 2; i <= n / 2; ++i) {
    if (n % i == 0) {
      factors.emplace_back(i);
      while (n % i == 0) {
        n /= i;
      }
    }
  }
  if (n > 1) {
    factors.emplace_back(n);
  }
  cache[n] = factors;
  return factors;
}

class ComputeTest : public ::testing::Test {};

TEST_F(ComputeTest, SmallNumbers) {
  EXPECT_EQ(getFactors(1), vector<int>{});
  EXPECT_EQ(getFactors(2), vector<int>{2});
  EXPECT_EQ(getFactors(3), vector<int>{3});
}

TEST_F(ComputeTest, LargeNumbers) {
  EXPECT_EQ(getFactors(100), vector<int>{2, 2, 5, 5});
  EXPECT_EQ(getFactors(1000), vector<int>{2, 2, 2, 5, 5, 5});
  EXPECT_EQ(getFactors(10000), vector<int>{2, 2, 2, 2, 5, 5, 5, 5});
}
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By using these techniques, the unit test can significantly improve its performance, allowing testing of more complex functions and larger Data sets for fast and stable testing.

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