License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.ECOOP.2020.16
URN: urn:nbn:de:0030-drops-131731
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2020/13173/
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Nielsen, Benjamin Barslev ; Møller, Anders

Value Partitioning: A Lightweight Approach to Relational Static Analysis for JavaScript

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LIPIcs-ECOOP-2020-16.pdf (0.7 MB)

Abstract

In static analysis of modern JavaScript libraries, relational analysis at key locations is critical to provide sound and useful results. Prior work addresses this challenge by the use of various forms of trace partitioning and syntactic patterns, which is fragile and does not scale well, or by incorporating complex backwards analysis. In this paper, we propose a new lightweight variant of trace partitioning named value partitioning that refines individual abstract values instead of entire abstract states. We describe how this approach can effectively capture important relational properties involving dynamic property accesses, functions with free variables, and predicate functions. Furthermore, we extend an existing JavaScript analyzer with value partitioning and demonstrate experimentally that it is a simple, precise, and efficient alternative to the existing approaches for analyzing widely used JavaScript libraries.

BibTeX - Entry

@InProceedings{nielsen_et_al:LIPIcs:2020:13173,
  author =	{Benjamin Barslev Nielsen and Anders M{\o}ller},
  title =	{{Value Partitioning: A Lightweight Approach to Relational Static Analysis for JavaScript}},
  booktitle =	{34th European Conference on Object-Oriented Programming (ECOOP 2020)},
  pages =	{16:1--16:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-154-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{166},
  editor =	{Robert Hirschfeld and Tobias Pape},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2020/13173},
  URN =		{urn:nbn:de:0030-drops-131731},
  doi =		{10.4230/LIPIcs.ECOOP.2020.16},
  annote =	{Keywords: JavaScript, dataflow analysis, abstract interpretation}
}

Keywords: JavaScript, dataflow analysis, abstract interpretation
Collection: 34th European Conference on Object-Oriented Programming (ECOOP 2020)
Issue Date: 2020
Date of publication: 06.11.2020

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