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Improving a website’s first meaningful paint by optimizing render blocking resources : An experimental case study

Web page loading time is one of the critical challenges on the Internet. This topic attracts more researchers as it largely reflects the user satisfaction. A web page resources typically consists of Hyper Text Markup Language (HTML), Cascading Style-Sheet (CSS), JavaScript (JS), media files, etc. As the complexity of the web page increases, the size of files fetched from server also increases which causes delay in transmitting, loading, parsing and rendering the web page. The web page is not rendered until HTML, CSS and JS files are loaded and parsed. Not all such files are needed to be rendered for the first page. Optimizing and loading only critical les required for the first page, can considerably reduce time taken to load the web page. After the first page is rendered, the rest of the files can be loaded and executed. In this thesis, we focus on improving the time taken for First Meaningful Paint(FMP) of website by loading the critical files initially. We used Design Science Research( DSR) methodology and created a PhantomJS application, to identify and segregate used and unused CSS for the first meaningful paint of the web page. We also analyzed script files to load only critical files required for FMP and the rest later. We evaluated our experiment by studying a case on Axis Communications AB and measured its website's performance to find if our experiment reduced FMP time. It showed improvement in time taken for FMP from 1284ms to 372.6ms. Based on the results, we suggest to web developers to separate and load the files required for FMP and load the rest of the files needed for the website later, so that the first page is rendered quickly.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:mau-20079
Date January 2017
CreatorsRashmi, Rashmi, Natarajan, Harini
PublisherMalmö högskola, Fakulteten för teknik och samhälle (TS), Malmö högskola/Teknik och samhälle
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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