# 题目
**编写一个函数,判断两个字符串是否是相互打乱的,也就是它们有着相同的字符,但是对应不同的顺序**
# 代码
```go
package main
import (
"fmt"
"os"
)
func disorder(s1, s2 string) bool { //判断两个字符串是否是相互打乱的
var count1, count2 int //count1 记录两个字符串中是否都有某个字符,
//count2 记录若都有这个字符,那么位置是否相等
if len(s1) != len(s2) { //若两个字符串不相等,那么肯定不是相互打乱的
return false
}
for index1, value1 := range s1 {
for index2, value2 := range s2 {
if value1 == value2 {
count1++ //对于s1中的某个字符,若s2有相等字符,则count1加1
if index1 == index2 {
count2++ //若不仅都有这个字符,而且位置也相等,则count2加1
}
break //既然在s2中找到了相等的字符,就进入s1下一个字符查找
}
if index2 == len(s2)-1 { //s2遍历到最后一个元素时,还找不到与s1相等的字符,则
return false //肯定不是相互打乱的
}
}
}
if count1 == count2 { //到这一步,说明s1和s2的字符相等,若位置相等的次数与字符相等
return false //的次数一样,说明s1和s2顺序一样,不是相互打乱的
}else{
return true
}
}
func main() {
a := disorder(os.Args[1], os.Args[2])
if a == true {
fmt.Printf("%s 和 %s 是相互打乱的", os.Args[1], os.Args[2])
}else {
fmt.Printf("%s 和 %s 不是相互打乱的", os.Args[1], os.Args[2])
}
}
```
# 测试
![base64图片](data:image/png;base64,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)
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