先看一个例子:

定义了一个类:

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" 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再定义一个类Test:

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" alt="" />

  • 当我们仅仅定义一个Test类对象test1时:

aaarticlea/png;base64,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" alt="" />

输出结果:

aaarticlea/png;base64,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" alt="" />

  • 此时如果用test1初始化一个Test类对象test2:

aaarticlea/png;base64,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" alt="" />

输出结果为:

aaarticlea/png;base64,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" alt="" />

原因在于,给test2初始化的时候调用了Test类中的复制构造函数,而这个复制构造函数中:

aaarticlea/png;base64,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" alt="" />

又有对成员的初始化列表,即对成员TestChild tc进行初始化,这里由于是对未初始化的对象进行初始化,所以使用了TestChild的复制构造函数。而tc=test.tc是对已经初始化的对象进行赋值,所以使用的是赋值操作符

  • 如果我们把Test类的复制构造函数改为:

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" alt="" />

此时再执行Test test2=test1,输出结果为:

aaarticlea/png;base64,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" alt="" />

因为,test2被test1初始化的时候调用了Test类的复制构造函数,而由于此时Test的复制构造函数没有初始化列表,Test类成员就使用的是TestChild tc的默认构造函数。而后再tc=test.tc中,由于tc已经被初始化,所以使用了赋值操作符

  • 如果再将复制构造函数改为:

aaarticlea/png;base64,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" alt="" />

此时再执行Test test2=test1,输出结果为:

aaarticlea/png;base64,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" alt="" />

因为,这里在Test的复制构造函数的初始化列表中对tc进行了初始化,所以就不会再用tc的默认构造函数初始化了。

  • 如果我们这里再对一个test3这样初始化:

aaarticlea/png;base64,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" alt="" />

重复前面三步,结果是完全一样的。虽然Test test2=test1和Test test3(test2)表面形式上来看不同,但是他们实际上做的事是相同的,这说明我们不能从表面上来判断它是调用的复制构造函数还是赋值操作符,而需要看具体执行的是什么操纵。如果执行的是自己初始化,那么使用的是默认构造函数;如果用别的对象对自己进行初始化,那么使用的是复制构造函数;如果自身已经初始化过,而用别的对象对自己进行赋值,那么使用的就是赋值操作符

  • 如果我们此时再多写一句:test3=test1,则会输出结果:

aaarticlea/png;base64,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" alt="" />

原因在于,test3是已经初始化过的对象,再对test3赋值,就调用了Test类的赋值操作符:

aaarticlea/png;base64,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" alt="" />

而Test类的赋值操作符中,又有对tc的赋值,因为test1也初始化过了,这里再对test1赋值就调用了TestChild类的赋值操作符。

全部代码如下:

class TestChild
{
public:
TestChild()
{
x = ;
y = ;
cout << "TestChild: Default Constructor!" << endl;
}
~TestChild(){}
TestChild(const TestChild& tc)
{
x = tc.x;
y = tc.y;
cout << "TestChild: Copy Constructor!" << endl;
} const TestChild& operator=(const TestChild& right)
{
x = right.x;
y = right.y;
cout << "TestChild:Assignment operator!" << endl;
return *this;
} int x, y;
}; class Test
{
public: Test(){ printf("Test: Default Constructor!\n"); }
explicit Test(const TestChild& tcc)
{
tc = tcc;
}
~Test(){}
/*Test(const Test& test) :tc(test.tc)//tc(test.tc),这里是对tc进行初始化,所以调动的是Copy Contrustor
{
tc = test.tc;//这里是赋值所以调用的是assignment operator
printf("Test: Copy Constructor!\n");
}*/ /*Test(const Test& test)
{
tc = test.tc;//先Construct tc,在对tc assignment operator
printf("Test: Copy Constructor!\n");
}*/ /*Test(const Test& test) :tc(test.tc)//这里直接用复制构造函数初始化,而忽略了下边TestChild tc
{
printf("Test: Copy Constructor!\n");
}*/ const Test & operator=(const Test& right)
{
tc = right.tc;//这里又有对数据成员tc的赋值,已经初始化过的tc再次赋值,此处也调用了
//TestChild的赋值操作符
printf("Test:Assignment operator!\n");
return *this;
} TestChild tc;
}; int main()
{
Test test1;//调用自身的默认构造函数;由于有成员TestChild,所以也会调用TestChild的默认构造函数 cout << "---------------------------------------------" << endl;
Test test2 = test1;//用test1构造一个不存在的test2,所以这里是调用的test2的复制构造函数; cout << "---------------------------------------------" << endl;
Test test3(test2); cout << "---------------------------------------------" << endl;
test3 = test1;
system("pause");
return ;
}

做一个总结,参考:http://bbs.csdn.net/topics/210020066

复制构造函数

拷贝构造函数,经常被称作X(X&),是一种特殊的构造函数,他由编译器调用来完成一些基于同一类的其他对象的构件及初始化。它的唯一的一个参数 (对象的引用)是不可变的(因为是const型的)。这个函数经常用在函数调用期间于用户定义类型的值传递及返回。拷贝构造函数要调用基类的拷贝构造函数 和成员函数。如果可以的话,它将用常量方式调用,另外,也可以用非常量方式调用。 
在C++中,下面三种对象需要拷贝的情况。因此,拷贝构造函数将会被调用。

1). 一个对象以值传递的方式传入函数体 
2). 一个对象以值传递的方式从函数返回 (对象传入函数和从函数返回一个对象,都是利用的对象的一个副本)
3). 一个对象需要通过另外一个对象进行初始化 
以上的情况需要拷贝构造函数的调用。(这三种情况其实都是执行的初始化

“一个用于构造对象(构造过程中的拷贝),一个用于拷贝对象(构造完成以后的拷贝)”

“用一个已存在的对象去构造一个不存在的对象(构造之前不存在),就是拷贝构造;用一个已存在的对象去覆盖另一个已存在的对象,就是赋值运算.

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