![]() And that will tell us a lot more about the text in the errors. So now we only have to send along two additional numbers along with our text. And then at the end, you’ll see that we still get the same checksum that we found earlier 1101, which becomes 81 when we do mod, and then the second checksum becomes 7336, which is 96 when we do them on. And we’ll continue this process until we’ve done all the letters. Likewise, we’ll add 108 to 173 to get 281, then we’ll add 281 to 245 to get 526. But now we will add this new checksum 173 to the value of 72 and the second checksum to get 245. So we’ll add 101 to the first checksum to get 173. The second character, the lowercase E is 101. ![]() So after the first character, they’re both the same. And then we will add that checksum value to the second checks up. So the first character, the capital H is a value 72. We’ll start with our same messages always and divided into blocks where each character is its own block. So let’s take a look at an example of how we would do Fletcher’s checksum. And then finally, while we’re done, we will calculate the values of the checksum mod 255 to reduce them to an eight bit binary value. And then we’ll add the new value of that checksum to the second checksum. And we’ll start with two checksums, one of them, C1 starts at zero, the other to also starts at zero, then for every block, we’ll add the value of the block to the first check sum. And we’ll just use the individual characters for this. Basically, the way it works is you divide the word into a sequence of equally sized blocks. And here we’re giving a quick pseudocode of the algorithm that is used to generate Fletcher’s checksum. ![]() Let’s look at an even better way to do a checksum to check and see if our data is correct. This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. 15.4 Error Checking - Fletcher's Checksum
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