License: Creative Commons Attribution 4.0 International license (CC BY 4.0)
When quoting this document, please refer to the following
DOI: 10.4230/DARTS.8.2.7
URN: urn:nbn:de:0030-drops-162052
URL: https://drops.dagstuhl.de/opus/volltexte/2022/16205/
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Chakraborty, Madhurima ; Olivares, Renzo ; Sridharan, Manu ; Hassanshahi, Behnaz

Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs (Artifact)

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DARTS-8-2-7.pdf (0.6 MB)
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DARTS-8-2-7-artifact-1eaa4ca32db3fae30f88df0963f950d8.ova (7,526 MB)

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The artifact has been evaluated as described in the ECOOP 2022 Call for Artifacts and the ACM Artifact Review and Badging Policy.


Abstract

Building sound and precise static call graphs for real-world JavaScript applications poses an enormous challenge, due to many hard-to-analyze language features. Further, the relative importance of these features may vary depending on the call graph algorithm being used and the class of applications being analyzed. In this paper, we present a technique to automatically quantify the relative importance of different root causes of call graph unsoundness for a set of target applications. The technique works by identifying the dynamic function data flows relevant to each call edge missed by the static analysis, correctly handling cases with multiple root causes and inter-dependent calls. We apply our approach to perform a detailed study of the recall of a state-of-the-art call graph construction technique on a set of framework-based web applications. The study yielded a number of useful insights. We found that while dynamic property accesses were the most common root cause of missed edges across the benchmarks, other root causes varied in importance depending on the benchmark, potentially useful information for an analysis designer. Further, with our approach, we could quickly identify and fix a recall issue in the call graph builder we studied, and also quickly assess whether a recent analysis technique for Node.js-based applications would be helpful for browser-based code. All of our code and data is publicly available, and many components of our technique can be re-used to facilitate future studies.

BibTeX - Entry

@Article{chakraborty_et_al:DARTS.8.2.7,
  author =	{Chakraborty, Madhurima and Olivares, Renzo and Sridharan, Manu and Hassanshahi, Behnaz},
  title =	{{Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs (Artifact)}},
  pages =	{7:1--7:5},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2022},
  volume =	{8},
  number =	{2},
  editor =	{Chakraborty, Madhurima and Olivares, Renzo and Sridharan, Manu and Hassanshahi, Behnaz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2022/16205},
  URN =		{urn:nbn:de:0030-drops-162052},
  doi =		{10.4230/DARTS.8.2.7},
  annote =	{Keywords: JavaScript, call graph construction, static program analysis}
}

Keywords: JavaScript, call graph construction, static program analysis
Collection: DARTS, Volume 8, Issue 1, Special Issue of the 34th Euromicro Conference on Real-Time Systems (ECRTS 2022)
Issue Date: 2022
Date of publication: 23.06.2022


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