JSAnalyzer

Paper @ACM TWEB 2022 (accepted)
JSAnalyzer: A Web Developer Tool for Simplifying Mobile Web Pages

JSAnalyzer is a an easy-to-use tool that enables web developers to quickly optimize JavaScript usage in their pages, and to generate simpler versions of these pages for mobile web users. JSAnalyzer is motivated by the widespread use of non-critical JavaScript elements, i.e., those that have negligible (if any) impact on the page’s visual content and interactive functionality. JSAnalyzer allows the developer to selectively enable or disable JavaScript elements in any given page while visually observing their impact on the page.

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slimWeb is a novel approach that automatically derives lightweight versions of mobile web pages on-the-fly by eliminating the use of unnecessary JavaScript. It consists of a JavaScript classification service powered by a supervised Machine Learning (ML) model that provides insights into each JavaScript element embedded in a web page. slimWeb aims to improve the web browsing experience by predicting the class of each element, such that essential elements are preserved and non-essential elements are blocked.

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QLUE (QuaLitative Uniform Evaluation) is a tool that automates the qualitative evaluation of web pages generated by web complexity solutions with respect to their original versions using computer vision. QLUE evaluates the content and the functionality of these pages separately using two metrics: QLUE's Structural Similarity, to assess the former, and QLUE's Functional Similarity to assess the latter---a task that is proven to be a challenging for humans given the complex functional dependencies in modern pages.

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Application Layer Congestion Control (ALCC) is a framework that allows any new CC protocol to be implemented easily at the application layer, within or above an application-layer protocol that sits atop a legacy TCP stack. It drives it to deliver approximately the same as the native performance. The ALCC socket sits on top of a traditional TCP socket. Still, it can leverage the large congestion windows opened by TCP connections to carefully execute an application-level CC within the window bounds of the underlying TCP connection.

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Model-Driven Interpretability (MDI) is congestion control framework, which derives a model version of a delay-based protocol by simplifying a congestion control protocol's response into a guided random walk over a two-dimensional Markov model. We demonstrate the case for the MDI framework by using MDI to analyze and interpret the behavior of two delay-based protocols over cellular channels: Verus and Copa.

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A tool that enables the automation of the qualitative evaluation of web pages using computer vision. In comparison to humans, PQual can effectively evaluate all the functionality of a web page, whereas the users might skip many of the functional elements during the evaluation.

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A JavaScript de-cluttering engine that aims at simplifying web pages without compromising the page content or functionality. JSCleaner uses a classification algorithm that classifies JavaScript into three main categories: non-critical, translatable, and critical scripts. JSCleaner removes the non-critical scripts from a web page, replaces the translatable scripts with their HTML outcomes, and preserves the critical scripts.

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An adaptive congestion control protocol designed for cellular networks. Verus leverages the relation ship between the sending window and the observed network delay by using the delay profile curve. Verus is a delay-based congestion control protocol.

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We are always on the look out for talented people to join the lab. Whether a research summer internship, a research visit, or a longer term position as a post-doc or research assistant. For inquiries please email yasir.zaki (at) nyu.edu.