To quickly create interactive web pages, developers heavily rely on (large) general-purpose JavaScript libraries. This practice bloats web pages with complex unused functions dead code which are unnecessarily downloaded and processed by the browser. The identification and the elimination of these functions is an open problem, which this paper tackles with Muzeel, a black-box approach requiring neither knowledge of the code nor execution traces. While the state-of-the-art solutions stop analyzing JavaScript when the page loads, the core design principle of Muzeel is to address the challenge of dynamically analyzing JavaScript after the page is loaded, by emulating all possible user interactions with the page, such that the used functions (executed when interactivity events fire) are accurately identified, whereas unused functions are filtered out and eliminated. We run Muzeel against 15,000 popular web pages and show that half of the 300,000 JavaScript files used in these pages have at least 70% of unused functions, accounting for 55% of the files' sizes. To assess the impact of dead code elimination on Mobile Web performance, we serve 200 Muzeel-ed pages to several Android phones and browsers, under variable network conditions. Our evaluation shows that Muzeel can speed up page loads by 25-30% thanks to a combination of lower CPU and bandwidth usage. Most importantly, we show that such savings are achieved while maintaining the pages' visual appearance and interactive functionality.

The amount of JavaScript used in web pages has substantially grown in the past decade, leading to large and complex pages that are computationally intensive for handheld mobile devices. Due to the increasing usage of these devices to access today’s web, and to accommodate the needs of a large number of mobile web users who solely rely on low-end devices, we propose “JSAnalyzer,” 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 to (1) accurately identify any non-critical JavaScript elements and (2) create a simplified page with these elements removed. Our quantitative evaluation shows that, given a low-end mobile phone, JSAnalyzer achieves an increase of nearly 90% in Google’s lighthouse performance score while reducing the page load time by 30%. A qualitative study of 22 users shows that the lighter pages produced by JSAnalyzer maintain more than 90% visual similarity compared to the original pages. Moreover, JSAnalyzer was evaluated by 69 developers, showing that it scores nearly 90% in terms of usefulness and usability while retaining the page’s content and functionality. Finally, we show that JSAnalyzer outperforms state-of-the-art solutions in terms of timing speedups and resource savings.