一、对象转型介绍
对象转型分为两种:一种叫向上转型(父类对象的引用或者叫基类对象的引用指向子类对象,这就是向上转型),另一种叫向下转型。转型的意思是:如把float类型转成int类型,把double类型转成float类型,把long类型转成int类型,这些都叫转型。把一种形式转成另外一种形式就叫转型。除了基础数据类型的转型之外(基础数据类型的转型:大的可以转成小的,小的也可以转成大的。),对象领域里面也有对象之间的转型。
1.1.对象转型实例一
1 package javastudy.summary;
2
3 /**
4 * 父类Animal
5 * @author gacl
6 *
7 */
8 class Animal {
9
10 public String name;
11
12 public Animal(String name) {
13 this.name = name;
14 }
15 }
16
17 /**
18 * 子类Cat继承Animal
19 * @author gacl
20 *
21 */
22 class Cat extends Animal {
23
24 /**
25 * Cat添加自己独有的属性
26 */
27 public String eyeColor;
28
29 public Cat(String n, String c) {
30 super(n);//调用父类Animal的构造方法
31 this.eyeColor = c;
32 }
33 }
34
35 /**
36 * 子类Dog继承Animal
37 * @author gacl
38 *
39 */
40 class Dog extends Animal {
41 /**
42 * Dog类添加自己特有的属性
43 */
44 public String furColor;
45
46 public Dog(String n, String c) {
47 super(n);//调用父类Animal的构造方法
48 this.furColor = c;
49 }
50
51 }
52
53 /**
54 * 下面是这三个类的测试程序
55 * @author gacl
56 *
57 */
58 public class TestClassCast {
59
60 /**
61 * @param args
62 */
63 public static void main(String[] args) {
64
65 Animal a = new Animal("name");
66 Cat c = new Cat("catname","blue");
67 Dog d = new Dog("dogname", "black");
68 /**
69 * a instanceof Animal这句话的意思是a是一只动物吗?
70 * a是Animal这个类里面的是一个实例对象,所以a当然是一只动物,其结果为true。
71 */
72 System.out.println(String.format("a instanceof Animal的结果是%s",a instanceof Animal));//true
73 /**
74 * c是Cat类的实例对象的引用,即c代表的就是这个实例对象,
75 * 所以“c是一只动物”打印出来的结果也是true。
76 * d也一样,所以“d是一只动物”打印出来的结果也是true。
77 */
78 System.out.println(String.format("c instanceof Animal的结果是%s",c instanceof Animal));//true
79 System.out.println(String.format("d instanceof Animal的结果是%s",d instanceof Animal));//true
80 /**
81 * 这里判断说“动物是一只猫”,不符合逻辑,所以打印出来的结果是false。
82 */
83 System.out.println(String.format("a instanceof Cat的结果是%s",a instanceof Cat));
84 /**
85 * 这句话比较有意思了,a本身是Animal类的实例对象的引用,
86 * 但现在这个引用不指向Animal类的实例对象了,而是指向了Dog这个类的一个实例对象了,
87 * 这里也就是父类对象的引用指向了子类的一个实例对象。
88 */
89 a = new Dog("bigyellow", "yellow");
90 System.out.println(a.name);//bigyellow
91 /**
92 * 这里的furColor属性是子类在继承父类的基础上新增加的一个属性,是父类没有的。
93 * 因此这里使用父类的引用对象a去访问子类对象里面新增加的成员变量是不允许的,
94 * 因为在编译器眼里,你a就是Animal类对象的一个引用对象,你只能去访问Animal类对象里面所具有的name属性,
95 * 除了Animal类里面的属性可以访问以外,其它类里面的成员变量a都没办法访问。
96 * 这里furColor属性是Dog类里面的属性,因此你一个Animal类的引用是无法去访问Dog类里面的成员变量的,
97 * 尽管你a指向的是子类Dog的一个实例对象,但因为子类Dog从父类Animal继承下来,
98 * 所以new出一个子类对象的时候,这个子类对象里面会包含有一个父类对象,
99 * 因此这个a指向的正是这个子类对象里面的父类对象,因此尽管a是指向Dog类对象的一个引用,
100 * 但是在编译器眼里你a就是只是一个Animal类的引用对象,你a就是只能访问Animal类里面所具有的成员变量,
101 * 别的你都访问不了。
102 * 因此一个父类(基类)对象的引用是不可以访问其子类对象新增加的成员(属性和方法)的。
103 */
104 //System.out.println(a.furColor);
105 System.out.println(String.format("a指向了Dog,a instanceof Animal的结果是%s",a instanceof Animal));//true
106 /**
107 * 这里判断说“a是一只Dog”是true。
108 * 因为instanceof探索的是实际当中你整个对象到底是什么东西,
109 * 并不是根据你的引用把对象看出什么样来判断的。
110 */
111 System.out.println(String.format("a instanceof Dog的结果是%s",a instanceof Dog));//true
112 /**
113 * 这里使用强制转换,把指向Animal类的引用对象a转型成指向Dog类对象的引用,
114 * 这样转型后的引用对象d1就可以直接访问Dog类对象里面的新增的成员了。
115 */
116 Dog d1 = (Dog)a;
117 System.out.println(d1.furColor);//yellow
118 }
119
120 }
运行结果:
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" 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内存分析
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****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" alt="" />
在内存中可以看到,指向Dog类实例对象的引用对象a是一个Animal类型的引用类型,这就比较有意思了,Animal类型指向了Dog这个对象,那么,在程序的眼睛里会把这只Dog当成一只普通的Animal,既然是把Dog当成一只普通的Animal,那么Dog类里面声明的成员变量furColor就不能访问了,因为Animal类里面没有这个成员变量。因此,从严格意义上来讲,这个a眼里只看到了这个子类对象里面的父类对象Animal,因此能访问得到的也只是这个Animal对象里面的name属性,而这个Animal对象外面的furColor属性是访问不到的,虽然Dog对象确实有这个属性存在,但a就是看不到,a门缝里看Dog——把Dog看扁了,不知道Dog还有furColor这个属性存在,因此a访问不了furColor属性,因此从严格意义上来讲,a指向的只是这个Dog对象里面的Animal对象,也就是黄色箭头指向的那部分,a就只看到了Dog里面这部分,而Dog外面的部分都看不到了。这就是父类引用指向子类对象,父类引用指向子类对象的时候,它看到的只是作为父类的那部分所拥有的属性和方法,至于作为子类的那部分它没有看到。
如果真的想访问Dog对象的furColor属性,那就采用对象转型的办法,把父类对象的引用转型成子类对象的引用。Dog d1 = (Dog)a;这里采用的就是对象转型的办法,把a强制转换成一只Dog对象的引用,然后将这个引用赋值给Dog型的引用变量d1,这样d1和a都是指向堆内存里面的Dog对象了,而且d1指向的就是这只Dog所有的部分了,通过这个d1就可以访问Dog对象里面所有的成员了。
1.2.对象转型实例二
1 public class TestClassCast {
2
3 public void f(Animal a) {
4 System.out.println(a.name);
5 if (a instanceof Cat) {
6 Cat cat = (Cat)a;
7 System.out.println(cat.eyeColor+" eye");
8 }else if (a instanceof Dog) {
9 Dog dog = (Dog)a;
10 System.out.println(dog.furColor+" fur");
11 }
12 }
13
14 /**
15 * @param args
16 */
17 public static void main(String[] args) {
18 Animal a = new Animal("name");
19 Cat c = new Cat("catname","blue");
20 Dog d = new Dog("dogname", "black");
21 TestClassCast testClassCast = new TestClassCast();
22 testClassCast.f(a);
23 testClassCast.f(c);
24 testClassCast.f(d);
25 }
26 }
这里的这些代码是对前面声明的三个类Animal,Dog,Cat测试的延续,这里我们在TestClassCast这里类里面测试这个三个类,这里我们在TestClassCast类里面new了一个testClassCast对象,为的是调用TestClassCast类里面声明的f(Animal a)这个方法,这个f()方法里面的参数类型是Animal类型,如果是Animal类型的参数,那么我们可以把这个Animal类型的子类对象作为参数传进去,这是可以的。如把一只Dog或者是一只Cat丢进f()方法里面这都是可以的,因为Dog和Cat也是Animal。因此当程序执行到testClassCast.f(a);,testClassCast.f(c);,testClassCast.f(d);的时候,因为f()方法里面的参数是Animal类型的,所以我们可以把一个Animal对象传进去,除此之外,我们还可以直接把从Animal类继承下来的Dog类和Cat类里面的Dog对象和Cat对象作为实参传递过去,即是把Animal类型的子类对象作为参数传进去。这里就体现出了继承和父类对象的引用可以指向子类对象的好处了,如果说没有继承关系的存在,如果说父类的引用不可以指向子类对象,那么我们就得要在Test类里面定义三个f()方法了,即要定义这样的f()方法:
f(Animal a)、f(Dog d)、f(Cat c)分别用来处理Animal、Dog和Cat,使用三个方法来处理,将来程序的扩展起来就不是很容易了,因为面向对象可以帮助我们这些年来编程苦苦追求的一个境界是可扩展性比较好。可扩展性比较好的一个典型例子就是说当你建好一个建筑之后或者是你写好这个程序之后,把这个主建筑给建好了,将来你要加一些其他的功能的时候,尽量不要去修改主结构,这叫可扩展性好,你盖了一座大楼,你现在要在大楼的旁边添加一个厨房,那你在它旁边一盖就行了,如果有人告诉你,我添加一个厨房我需要把你整个大楼的主要柱子都给拆了然后再盖一遍,这你干吗,肯定不干。如果结构设计成这样,那就是设计得不好,可扩展性不好。所以这里如果要把f()方法写成三个重载的f()方法,那么将来我输出一只鸟的时候又得要添加一个f(Bird b)方法来处理鸟。这样扩展起来就太麻烦了,因为每处理一只动物都要添加一个新的方法,但是如果存在继承关系,如果父类对象的引用可以指向子类对象,那扩展起来就简单了,你可以把处理动物的方法写在一个方法f(Animal a)里面就够了,因为所有动物的种类都是从Animal类继承下来,因此给f()方法传递Animal类型的参数的时候可以直接把这个Animal类的子类对象传进去,这样不管是要增加什么动物的输出,我都可以调用f(Animal a)方法去处理,这种扩展性比每次都要增加一个新的处理方法的扩展性要好得多,这就是继承的一个好处,这就是对象转型对于可扩展性来的好处:“对象的引用可以指向子类对象”,是因为面向对象的编程里面存在这样的继承关系,使得程序的可扩展性比较好。
对象转型可以使父类对象的引用可以指向子类对象,给程序带来了比较好的可扩展性:我们可以在一个方法的参数里面定义父类的引用,然后实际当中传的时候传的是子类的对象,然后我们再在方法里面判断这个传过来的子类对象到底属于哪个子类,然后再去执行这个子类里面的方法或者调用这个子类里面的成员变量,因此程序的可扩展性比单独定义好多个方法要好一些。不过这个可扩展性还没有达到最好,使用多态就可以让程序的扩展性达到极致。
转自:http://www.cnblogs.com/xdp-gacl/p/3647810.html