# Write a loop invariant

One problem might be that the information that we have gained after the loop is not exacly what we wanted to compute, but we are using it to get our final result. The list below is not meant to be complete, and also one strategy might work better for you then another.

Example: Selection Sort. They are a simple yet powerful tool to help understand iterative code. Here is the general idea. Initialization : Prior to the first iteration.

### Loop invariant geeksforgeeks

Your second point seem slightly artificial to me though. To prove Insertion Sort is correct, you will then demonstrate it for the three stages: Initialization - The subarray starts with the first element of the array, and it is obviously sorted to begin with. Note that [a,b means all integers from a to b, including a, but not including b. Here headway is obious: numSorted is incremented each time through the loop. Sometimes the reasoning behind termination is more difficult. There are two advantages to this: Work is not carried forward to the next pass in complicated, data dependent ways. In the outer loop, array is sorted for first i elements. We can assume that the invariant holds before the loop, i. Think about: What you want to know at the end? Each time through the loop increased numSorted by one. Maintenance - Each iteration of the loop expands the subarray, but keeps the sorted property. Merging this into the incomplete loop invariant from above, this would state.

In these cases, the loop invariant is often a statement of the form: The solution computed so far, is the correct solution for the things that I have seen so far.

In our algorithm above, we have a variable answer, which we manipulate while the loop is running. Check that each time through the loop, assuming the Loop Invariant true going into the loop, it is true going out of the loop; Check that headway towards termination is being made. I've edited my answer. Before we look at how to handle them, lets remind ourselves, why they together constitute a proof.

## Loop invariant for linear search

But how would you prove that the code is correct? Loop Invariant condition of various algorithms: Prerequisite: insertion sort , selection sort , quick sort , bubblesort , Selection Sort: In selection sort algorithm we find the minimum element from the unsorted part and put it at the beginning. When doing so we can assume that the invariant holds at the beginning of the loop. So you have to be careful. This function was presented in the previous example. The combination of the loop invariant and the termination condition gives that smallestSoFar is the index of the smallest value in the array. OR how do we know that building of max heap actually builds a max heap! The children of node i are numbered higher than i. Pivot element is placed at its correct position.

Answer updated. Elements less than pivot element lie on the left side of pivot element. Each time through the loop increased numSorted by one.

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