
JavaScript is becoming the de-facto programming language of the Web. Large-scale web applications (web apps) written in Javascript are commonplace nowadays, with big technology players (e.g., Google, Facebook) using it in their core flagship products. Today, it is common practice to reuse existing JavaScript code, usually in the form of third-party libraries and frameworks. If on one side this practice helps in speeding up development time, on the other side it comes with the risk of bringing dead code, i.e., JavaScript code which is never executed, but still downloaded from the network and parsed in the browser. This overhead can negatively impact the overall performance and energy consumption of the web app. In this paper we present Lacuna, an approach for JavaScript dead code elimination, where existing JavaScript analysis techniques are applied in combination. The proposed approach supports both static and dynamic analyses, it is extensible, and independent of the specificities of the used JavaScript analysis techniques. Lacuna can be applied to any JavaScript code base, without imposing any constraints to the developer, e.g., on her coding style or on the use of some specific JavaScript feature (e.g., modules). Lacuna has been evaluated on a suite of 29 publicly-available web apps, composed of 15,946 JavaScript functions, and built with different JavaScript frameworks (e.g., Angular, Vue.js, jQuery). Despite being a prototype, Lacuna obtained promising results in terms of analysis execution time and precision.
SDG 7 - Affordable and Clean Energy
SDG 7 - Affordable and Clean Energy
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| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
