循环不变量是在循环执行前后为真的断言。

不变的意思是永不改变

这里循环不变量的意思是“发生在循环中的变量的变化(增加或减少)并没有改变循环条件，即条件是满足的”，因此循环不变量的概念就产生了

循环不变量属性是一个条件，适用于循环执行的每一步。For循环，while循环，等等)

这对于循环不变证明是必不可少的，如果在执行的每一步都保持循环不变属性，则可以证明算法正确执行。

对于一个正确的算法，循环不变量必须保持在:

初始化(开始)

维护(之后的每一步)

终止(当它完成时)

这被用来计算很多东西，但最好的例子是加权图遍历的贪婪算法。对于贪心算法产生最优解(穿过图的路径)，它必须达到连接所有节点在最小权值路径可能。

因此，循环不变的性质是所选择的路径具有最小的权值。在开始时，我们没有添加任何边，所以这个属性为真(在这种情况下，它不是假的)。在每一步中，我们都遵循最小权值边(贪婪步)，所以我们再次采用最小权值路径。最后，我们找到了最小加权路径，所以我们的性质也是成立的。

如果一个算法不这样做，我们可以证明它不是最优的。

在处理循环和不变量时，有一件事很多人没有马上意识到。他们混淆了循环不变量和循环条件(控制循环终止的条件)。

正如人们指出的那样，循环不变量必须为真

在循环开始之前 在每次循环迭代之前 在循环结束之后

(尽管在循环体期间它可以暂时为假)。另一方面，循环条件在循环结束后必须为false，否则循环将永远不会终止。

因此循环不变量和循环条件必须是不同的条件。

复杂循环不变量的一个很好的例子是用于二分搜索。

bsearch(type A[], type a) {
start = 1, end = length(A)

    while ( start <= end ) {
        mid = floor(start + end / 2)

        if ( A[mid] == a ) return mid
        if ( A[mid] > a ) end = mid - 1
        if ( A[mid] < a ) start = mid + 1

    }
    return -1

}

因此循环条件看起来非常简单——当开始>结束时，循环终止。但是为什么循环是正确的呢?什么是循环不变量来证明它的正确性?

不变量是逻辑语句:

if ( A[mid] == a ) then ( start <= mid <= end )

这句话是逻辑重言——在我们试图证明的特定循环/算法的上下文中，它总是正确的。并且在循环结束后，它提供了关于循环正确性的有用信息。

If we return because we found the element in the array then the statement is clearly true, since if A[mid] == a then a is in the array and mid must be between start and end. And if the loop terminates because start > end then there can be no number such that start <= mid and mid <= end and therefore we know that the statement A[mid] == a must be false. However, as a result the overall logical statement is still true in the null sense. ( In logic the statement if ( false ) then ( something ) is always true. )

那么我说的循环条件在循环结束时必然为假呢?当在数组中找到元素时，循环条件在循环结束时为true !?实际上不是，因为隐含的循环条件实际上是while (A[mid] != A && start <= end)，但我们缩短了实际的测试，因为第一部分是隐含的。这个条件在循环结束后明显为false，而不管循环如何结束。

循环不变量是在循环执行前后为真的断言。

It is hard to keep track of what is happening with loops. Loops which don't terminate or terminate without achieving their goal behavior is a common problem in computer programming. Loop invariants help. A loop invariant is a formal statement about the relationship between variables in your program which holds true just before the loop is ever run (establishing the invariant) and is true again at the bottom of the loop, each time through the loop (maintaining the invariant). Here is the general pattern of the use of Loop Invariants in your code:

... // the Loop Invariant must be true here while ( TEST CONDITION ) { // top of the loop ... // bottom of the loop // the Loop Invariant must be true here } // Termination + Loop Invariant = Goal ... Between the top and bottom of the loop, headway is presumably being made towards reaching the loop's goal. This might disturb (make false) the invariant. The point of Loop Invariants is the promise that the invariant will be restored before repeating the loop body each time. There are two advantages to this:

Work is not carried forward to the next pass in complicated, data dependent ways. Each pass through the loop in independent of all others, with the invariant serving to bind the passes together into a working whole. Reasoning that your loop works is reduced to reasoning that the loop invariant is restored with each pass through the loop. This breaks the complicated overall behavior of the loop into small simple steps, each which can be considered separately. The test condition of the loop is not part of the invariant. It is what makes the loop terminate. You consider separately two things: why the loop should ever terminate, and why the loop achieves its goal when it terminates. The loop will terminate if each time through the loop you move closer to satisfying the termination condition. It is often easy to assure this: e.g. stepping a counter variable by one until it reaches a fixed upper limit. Sometimes the reasoning behind termination is more difficult.

应该创建循环不变量，以便当达到终止条件时，且不变量为真，则达到目标:

不变+终止=>目标 它需要实践来创建简单而相关的不变式，这些不变式捕获了除了终止之外的所有目标实现。最好使用数学符号来表示循环不变量，但当这导致过于复杂的情况时，我们依赖于清晰的散文和常识。