Code Minification and Raster File Compression as Performance Improvement Methods – a Case Study - Karol KROL (Communications of International Proceedings, 2021)
The increasing technological advancement of websites and web applications continually drives up the amount of data they download. Hence, the role of performance optimisation grows. The objective of the paper is to analyse the impact of optimisation of a map component’s subcomponents on its performance. The investigated web application is a prototype of an ‘interactive lens’. Three application variants were prepared: 1) before optimisation (basic version), 2) with a compressed raster file, 3) with a compressed raster file and minified code. Performance testing was conducted using GTMetrix and Dareboost. Application performance was represented by selected quality metrics, such as Performance Score, Largest Content Element (LCP), Total Blocking Time (TBT), and Speed Index (SI). The optimisation of resources yielded a significant improvement in the map component’s performance. The LCP metric fell from 2.1 s to 1.6 s. Raster compression reduced SI to 884 from 1635 units. The research noted the consequences of image file compression, which may deteriorate its visual quality. It confirmed that reduced file size (compression and/or minification) affects web application performance, which improves its usability.
Keywords: optimisation; compression; minification; performance; usability; interactive lens; network resources.