之前的回答已经很好地定义了循环不变量。

以下是CLRS的作者如何使用循环不变量来证明插入排序的正确性。

插入排序算法(见书):

INSERTION-SORT(A)
    for j ← 2 to length[A]
        do key ← A[j]
        // Insert A[j] into the sorted sequence A[1..j-1].
        i ← j - 1
        while i > 0 and A[i] > key
            do A[i + 1] ← A[i]
            i ← i - 1
        A[i + 1] ← key

循环不变量在这种情况下: 子数组[1到j-1]始终被排序。

现在让我们检查一下，证明这个算法是正确的。

初始化:在第一次迭代j=2之前。所以子数组[1:1]就是要测试的数组。因为它只有一个元素，所以它是有序的。这样不变性就被满足了。

维护:这可以通过在每次迭代后检查不变量来轻松验证。在这种情况下，它被满足了。

终止:这是我们将证明算法正确性的步骤。

当循环结束时，j=n+1。循环不变量再次被满足。这意味着子数组[1到n]应该排序。

这就是我们想用算法做的。因此，我们的算法是正确的。

之前的回答已经很好地定义了循环不变量。

以下是CLRS的作者如何使用循环不变量来证明插入排序的正确性。

插入排序算法(见书):

INSERTION-SORT(A)
    for j ← 2 to length[A]
        do key ← A[j]
        // Insert A[j] into the sorted sequence A[1..j-1].
        i ← j - 1
        while i > 0 and A[i] > key
            do A[i + 1] ← A[i]
            i ← i - 1
        A[i + 1] ← key

循环不变量在这种情况下: 子数组[1到j-1]始终被排序。

现在让我们检查一下，证明这个算法是正确的。

初始化:在第一次迭代j=2之前。所以子数组[1:1]就是要测试的数组。因为它只有一个元素，所以它是有序的。这样不变性就被满足了。

维护:这可以通过在每次迭代后检查不变量来轻松验证。在这种情况下，它被满足了。

终止:这是我们将证明算法正确性的步骤。

当循环结束时，j=n+1。循环不变量再次被满足。这意味着子数组[1到n]应该排序。

这就是我们想用算法做的。因此，我们的算法是正确的。

在线性搜索(根据书中给出的练习)中，我们需要在给定的数组中找到值V。

它很简单，从0 <= k < length开始扫描数组并比较每个元素。如果找到V，或者扫描到数组的长度，就终止循环。

根据我对上述问题的理解-

循环不变量(初始化): 在k - 1迭代中找不到V。第一次迭代，这是-1因此我们可以说V不在-1位置

保养: 在下一次迭代中，V不在k-1中成立

Terminatation: 如果V位于k个位置，或者k达到数组的长度，则终止循环。

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。

在这种情况下，不变量意味着在每次循环迭代的某一点上必须为真条件。

在契约编程中，不变量是在调用任何公共方法之前和之后必须为真(通过契约)的条件。