Measuring the Impact of Web Performance Issues on Visual Progression Based User Experience

Abstract

Performance issues in loading web page contents and developing them such way that these becomes start interacting with users in fastest possible time has been a massive challenge for businesses over the years. Any medium to large sized web application may have several web pages and each of them may have several performance issues. One can fix them all but in perspective of meeting deadlines and allocating budget it can be cumbersome. The main objective of this research is to measure the impact of those performance issues that are creating massive impact in terms of other websites based on visual progression and developing a Continuous Integration, Continuous Development tool as a part of GitHub Actions marketplace to recommend developers and companies on prioritizing issues across various pages within their public and private repositories. This project based research follows quantitative research methodology including data collection, exploratory analysis of data, selection of features in uni-variate and wrapper techniques as well as re-sampling through traintest-split and K-fold cross validation techniques in several regression algorithms. We have developed a REST API by using dotnet framework to serve it as a service. Finally, we developed a GitHub Actions by using JavaScript on Node.js runtime to preview predictions on prioritization in several pages like a recommendation tool. This research shows time to interactive, boot-up time and largest contentful paint are the most important metrics in terms of boosting a site’s visual progression based experience. This research is expandable in terms of other user experiences as well as the project in terms of authorization mechanism.