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In C, function parameters can be passed by value, passing a copy of the parameter, or passed by reference, directly accessing the original memory of the parameter. When passing by reference, changes made to parameters by a function are reflected directly in the caller. For example, passing parameters by reference can optimize performance, especially when dealing with large data structures, and avoid additional memory allocation and copy overhead.
C Memory allocation method for function reference parameters
In C, function parameters can be passed by value or by reference. When passing by value, a copy of the argument is passed to the function, whereas when passing by reference, the function uses the original memory address of the argument directly.
Pass by value
void incrementValue(int value) { value++; // 改变的是 value 的副本,不会影响原始变量 } int main() { int number = 5; incrementValue(number); cout << number << endl; // 仍然输出 5 }
Pass by reference
void incrementValue(int& value) { value++; // 改变的是原始变量 } int main() { int number = 5; incrementValue(number); cout << number << endl; // 输出 6 }
In the above example, incrementValue
The function is passed the value
parameter by reference. This means that the function operates directly on the original variable, so any changes made to it will be reflected in the function caller.
Practical case:
Imagine a scenario where you need to write a function to calculate the dot product of two vectors. Passing by value will require creating two copies of the vector, resulting in additional memory allocation and slower performance. Instead, passing a vector by reference avoids memory allocation, thus improving performance.
double dotProduct(const vector<double>& a, const vector<double>& b) { double sum = 0.0; for (size_t i = 0; i < a.size(); i++) { sum += a[i] * b[i]; } return sum; } int main() { vector<double> a = {1.0, 2.0, 3.0}; vector<double> b = {4.0, 5.0, 6.0}; cout << dotProduct(a, b) << endl; // 输出 32.0 }
In this case, passing the vector by reference avoids creating a copy, thus improving the performance of computing the dot product.
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