@inproceedings{89efc54b81874182ab8589c67d91f3cd,
title = "PTDETECTOR: An Automated JavaScript Front-end Library Detector",
abstract = "Identifying what front-end library runs on a web page is challenging. Although many mature detectors exist on the market, they suffer from false positives and the inability to detect libraries bundled by packers such as Webpack. Most importantly, the detection features they use are collected from developers' knowledge leading to an inefficient manual workflow and a large number of libraries that the existing detectors cannot detect. This paper introduces PTDETECTOR, which provides the first automated method for generating features and detecting libraries on web pages. We propose a novel data structure, the pTree, which we use as a detection feature. The pTree is well-suited for automation and addresses the limitations of existing detectors. We implement PTDETECTOR as a browser extension and test it on 200 top-traffic websites. Our experiments show that PTDETECTOR can identify packer-bundled libraries, and its detection results outperform existing tools.",
keywords = "Front end, JavaScript, Library Detection, Web",
author = "Xinyue Liu and Lukasz Ziarek",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023 ; Conference date: 11-09-2023 Through 15-09-2023",
year = "2023",
doi = "10.1109/ASE56229.2023.00049",
language = "English",
series = "Proceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "649--660",
booktitle = "Proceedings - 2023 38th IEEE/ACM International Conference on Automated Software Engineering, ASE 2023",
address = "United States",
}