COMPARISON OF OPTIMIZATION TECHNIQUES: RESOURCE COMPRESSION, CACHING, JAVASCRIPT MINIFICATION

Abstract

The article examines various optimization techniques for web applications and conducts a comparative analysis of them in order to determine the most effective methods of increasing productivity. In the conditions of the rapid development of Internet technologies and the growing demands of users for the speed of loading web pages, the issue of optimization becomes extremely relevant. The high performance of web applications directly affects the user experience, the level of user engagement and the commercial success of web services. The research details resource compression methods (images, CSS, JavaScript), the use of server and client caching, JavaScript minification and optimization, as well as page load optimization techniques such as lazy loading, preloading, and prioritization of critical resources.

The focus is on the effectiveness of each technique in different environments, including different types of web applications (informational, commercial, social) and infrastructure (server, client, hybrid). The impact of optimization on user experience is considered, in particular on page load time, time to the first interaction (Time to Interactive), as well as the overall smoothness of web applications. The comparison is based on experimental data obtained using performance analysis tools such as Google Lighthouse, WebPageTest, GTmetrix and others.

The results of the study show that combining different optimization techniques can provide a significant improvement in the performance of web applications. For example, using caching combined with JavaScript and CSS minification has the biggest impact on load speed. At the same time, the optimization of images using modern formats (WebP, AVIF) and the introduction of lazy loading effectively reduce the volume of transferred data, which is especially important for mobile users with limited network bandwidth. Other techniques, such as using a CDN (Content Delivery Network) and optimizing database queries, also show high potential in improving performance.

Based on the obtained results, practical recommendations for developers regarding the implementation of optimization measures depending on the specifics of web applications are provided. In particular, developers are encouraged to conduct regular performance audits, use modern tools for monitoring and analysis, and implement automated optimization processes in their workflow.

The study highlights the need for a comprehensive approach to web application optimization that includes both technical and organizational aspects. Prospects for further research in this area are identified, in particular in the direction of automation of optimization processes using machine learning and artificial intelligence tools that can dynamically adjust performance parameters depending on the real operating conditions of web applications.