As the availability and popularity of the Internet continues to grow, the trend ofproviding global access to business resources and services online is an efficient andprofitable way for organizations to acquire a new share of the market. Due to the flexibilityand scalability of modern web technologies, web-based applications processand store personal or critical information in enormous amounts. Hence, the overallapplication’s functionality and secure data processing are the main key factors ofeach web application. For ensuring those key factors, the web page code must be regularlymonitored to retain the overall quality of the code. This project is devoted tochange identification and classification in modern web-based applications, based onthe comparison of two versions of web page code, acquired in different time periods.The foundation of the development is described as a detection algorithm in one of theacademic papers. The algorithm was supplemented by a more extensive classificationof changes that was originally proposed by the author. The result of the researchis a semi-automatic tool, developed in Python. The tool compares two versions ofthe web page code to find changes and classify those changes. The result of the tool’sexecution is a report file that contains statistics of the overall algorithm’s executionand type-clustered information about the detected changes between two versions ofthe web page code. The analysis of results showed that the implemented diff-toolprovides reliable results and allocates all types of possible changes in the web pagecodes, which are acknowledged by statistical analysis. The comparative analysis ofthe results of the developed diff-tool with the results of other similar technical solutionsrevealed serious shortcomings of other solutions, due to their data processingimplementation, classification of the changes and resulting report file.