Evaluating Quality Attributes in Web Development: A Comparative Study of Rendering Strategies
DOI:
https://doi.org/10.5753/jserd.2026.8015Keywords:
Client-Side Rendering, Server-Side Rendering, Performance Analysis, User Experience, Web ApplicationsAbstract
Modern web development identifies the rendering strategy as a critical architectural choice, directly impacting performance and user experience. This study compares the performance of Client-Side Rendering (CSR) and Server-Side Rendering (SSR) in web applications under varying JSON payload sizes. We evaluated performance based on Google’s Core Web Vitals (CWV) metrics, including Largest Contentful Paint (LCP), First Contentful Paint (FCP), Speed Index (SI), Time to Interactive (TTI), and JS Heap Size. We implemented a controlled environment using a photo gallery application and automated measurements via Lighthouse and Puppeteer across five data sizes: Extra Small (XS), Small (S), Medium (M), Large (L), and Extra Large (XL). The experiment was expanded to include six experimental conditions, incorporating JSON minification and Gzip compression as optimization techniques. The statistical analysis involved the Kruskal–Wallis test, pairwise Mann–Whitney U tests with Holm correction, and Cliff’s Delta as the effect size measure. Results indicate that SSR outperformed CSR in LCP and TTI across all data sizes. Conversely, CSR maintained a stable FCP regardless of the data volume. Gzip compression was the most impactful optimization. It reduced the median LCP by up to 86.7% for CSR and 93.0% for SSR on the Extra Large payload. SSR with Gzip was up to 7.9× faster than the optimized CSR in terms of LCP for the largest payload. These findings characterize the trade-offs between a controlled implementation of client-side JSON rendering and server-side pre-rendered HTML, and should not be interpreted as a complete evaluation of modern production frameworks (e.g., Next.js, Nuxt, SvelteKit, React, Vue) that employ hydration, streaming SSR, or partial/island architectures. Within this scope, these findings guide software engineers in choosing the most appropriate rendering strategy based on performance objectives and application data volume.
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Copyright (c) 2026 Joey Clapton, João Pedro Oliveira Batisteli, Hugo Bastos de Paula, Danilo Boechat Seufitelli, Cleiton Tavares
This work is licensed under a Creative Commons Attribution 4.0 International License.
