The initialize list of C++ Class
性能问题之外,有些时场合初始化列表是不可或缺的,以下几种情况时必须使用初始化列表
- 常量成员,因为常量只能初始化不能赋值,所以必须放在初始化列表里面
Error1(constchar* constmsg) :data(msg)
{
//data = msg;
}
- 引用类型,引用必须在定义的时候初始化,并且不能重新赋值,所以也要写在初始化列表里面
- 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" alt="" />
- 没有默认构造函数的类类型,因为使用初始化列表可以不必调用默认构造函数来初始化,而是直接调用拷贝构造函数初始化。
classError2
{
constchar* const data;
public:
Error2(constchar* constmsg = 0) :data(msg){}//Error2()
};
classError1
{
constchar* const data;
Error2 e2;
public:
Error1(constchar* constmsg=0) :data(msg)
{
// e2 = e2Out;
//data = msg;
}
//Error1(const char* const msg = 0) :data(msg){}
Error1(constchar* constmsg, Error2 & e2Out) :data(msg), e2(e2Out)
{
//e2 = e2Out;
//data = msg;
}
};
if not, there will be a waring,
- 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" alt="" />
- 但是对于类类型来说,最好使用初始化列表,为什么呢?由上面的测试可知,使用初始化列表少了一次调用默认构造函数的过程,这对于数据密集型的类来说,是非常高效的。同样看上面的例子,我们使用初始化列表来实现Test2的构造函数
struct Test2
{
Test1 test1 ;
Test2(Test1 &t1):test1(t1){}
}
- 但是对于类类型来说,最好使用初始化列表,为什么呢?由上面的测试可知,使用初始化列表少了一次调用默认构造函数的过程,这对于数据密集型的类来说,是非常高效的。同样看上面的例子,我们使用初始化列表来实现Test2的构造函数
使用同样的调用代码,输出结果如下。
第一行输出对应 调用代码的第一行。第二行输出对应Test2的初始化列表,直接调用拷贝构造函数初始化test1,省去了调用默认构造函数的过程。所以一个好的原则是,能使用初始化列表的时候尽量使用初始化列表。
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