Tajkia R. Toma

Work place: Institute of Information Technology, University of Dhaka, Dhaka, Bangladesh

E-mail: tajkiatoma@gmail.com

Website:

Research Interests: Software Design, Software Engineering, Combinatorial Optimization

Biography

Tajkia R. Toma completed her M.Sc. in Software Engineering from Institute of Information Technology, University of Dhaka, Bangladesh in 2014. She received her Bachelor’s degree in Information Technology (Major in Software Engineer-ing) from the same institute in 2012. Cur-rently she is working as a Software Engi-neer at Jantrik Technologies Ltd. Bangla-desh. Her research interest includes code analysis for web ap-plications and software design optimization. She received fel-lowship from the Ministry of Post, Telecommunications and Information Technology, Bangladesh for her M.Sc. thesis.

Author Articles
A Dependency Graph Generation Process for Cli-ent-side Web Applications

By Tajkia R. Toma Mohayeminul Islam Mohammad Shoyaib Md. Shariful Islam

DOI: https://doi.org/10.5815/ijieeb.2015.02.06, Pub. Date: 8 Mar. 2015

The prolific growth of the Internet density has replaced native applications with web based applications. Current trend of web applications is moving towards fat client architecture, which results in a large codebase of the client side of web applications. Manual management of this huge code is tedious and time consuming for de-velopers. We present a technique to construct a depend-ency graph to provide an overview of the code showing the inter-dependency of the code elements. We conduct a dynamic analysis to make the JavaScript call graph to address the dynamic nature of JavaScript. We further integrate HTML and CSS with the JavaScript call graph to make a dependency graph. Because we can accurately identify the HTML and CSS relations, the result of the dependency graph depends on the JavaScript call graph. Our evaluation of the JavaScript call graph on six web applications demonstrates that the precision is high for the large applications and relatively low for small applications. The recall is low for large applications and relatively higher for small applications.

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