Text Compare and Grouping Program using Dynamic Programming Algorithm

Abstract

Programming classes are now commonly found at both the high school and university levels. However, when learning this field, the copying program code problem is always a big issue. As a result, the author comes up with the idea of developing software that can compare the similarity of text as a group to determine the program code's similarity. A dynamic programming (DP) approach can solve the text comparison problem, which is also known as the Longest Common Subsequence (LCS) problem. To decrease the number of comparison characters, a grouping algorithm was introduced, and a token table was employed. The program can function as intended after the development is completed. Which can be used to compare and group file. With the grouping method presented, the number of comparisons was decreased. The number of the text to be compared was reduced by an average of 33.58 percent, making the program more efficient.