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。

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。

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。

简单地说，循环不变量是对循环的每次迭代都成立的某个谓词(条件)。例如，让我们看一个简单的For循环，它是这样的:

int j = 9;
for(int i=0; i<10; i++)  
  j--;

在这个例子中，i + j == 9(对于每个迭代)是正确的。一个较弱的不变式也是成立的 I >= 0 && I <= 10。

除了这些不错的答案，我想Jeff Edmonds在《如何思考算法》(How to Think About Algorithms)中举的一个很好的例子可以很好地说明这个概念:

EXAMPLE 1.2.1 "The Find-Max Two-Finger Algorithm" 1) Specifications: An input instance consists of a list L(1..n) of elements. The output consists of an index i such that L(i) has maximum value. If there are multiple entries with this same value, then any one of them is returned. 2) Basic Steps: You decide on the two-finger method. Your right finger runs down the list. 3) Measure of Progress: The measure of progress is how far along the list your right finger is. 4) The Loop Invariant: The loop invariant states that your left finger points to one of the largest entries encountered so far by your right finger. 5) Main Steps: Each iteration, you move your right finger down one entry in the list. If your right finger is now pointing at an entry that is larger then the left finger’s entry, then move your left finger to be with your right finger. 6) Make Progress: You make progress because your right finger moves one entry. 7) Maintain Loop Invariant: You know that the loop invariant has been maintained as follows. For each step, the new left finger element is Max(old left finger element, new element). By the loop invariant, this is Max(Max(shorter list), new element). Mathe- matically, this is Max(longer list). 8) Establishing the Loop Invariant: You initially establish the loop invariant by point- ing both fingers to the first element. 9) Exit Condition: You are done when your right finger has finished traversing the list. 10) Ending: In the end, we know the problem is solved as follows. By the exit condi- tion, your right finger has encountered all of the entries. By the loop invariant, your left finger points at the maximum of these. Return this entry. 11) Termination and Running Time: The time required is some constant times the length of the list. 12) Special Cases: Check what happens when there are multiple entries with the same value or when n = 0 or n = 1. 13) Coding and Implementation Details: ... 14) Formal Proof: The correctness of the algorithm follows from the above steps.