2 Search Results for "Chakraborty, Madhurima"

Document
Artifact
DOI: 10.4230/DARTS.8.2.7
Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs (Artifact)

Authors: Madhurima Chakraborty, Renzo Olivares, Manu Sridharan, and Behnaz Hassanshahi

Published in: DARTS, Volume 8, Issue 2, Special Issue of the 36th European Conference on Object-Oriented Programming (ECOOP 2022)

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.
Cite as

Madhurima Chakraborty, Renzo Olivares, Manu Sridharan, and Behnaz Hassanshahi. Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs (Artifact). In Special Issue of the 36th European Conference on Object-Oriented Programming (ECOOP 2022). Dagstuhl Artifacts Series (DARTS), Volume 8, Issue 2, pp. 7:1-7:5, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@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-dev.dagstuhl.de/entities/document/10.4230/DARTS.8.2.7},
  URN =		{urn:nbn:de:0030-drops-162052},
  doi =		{10.4230/DARTS.8.2.7},
  annote =	{Keywords: JavaScript, call graph construction, static program analysis}
}
Document
DOI: 10.4230/LIPIcs.ECOOP.2022.3
Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs

Authors: Madhurima Chakraborty, Renzo Olivares, Manu Sridharan, and Behnaz Hassanshahi

Published in: LIPIcs, Volume 222, 36th European Conference on Object-Oriented Programming (ECOOP 2022)

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.
Cite as

Madhurima Chakraborty, Renzo Olivares, Manu Sridharan, and Behnaz Hassanshahi. Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs. In 36th European Conference on Object-Oriented Programming (ECOOP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 222, pp. 3:1-3:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{chakraborty_et_al:LIPIcs.ECOOP.2022.3,
  author =	{Chakraborty, Madhurima and Olivares, Renzo and Sridharan, Manu and Hassanshahi, Behnaz},
  title =	{{Automatic Root Cause Quantification for Missing Edges in JavaScript Call Graphs}},
  booktitle =	{36th European Conference on Object-Oriented Programming (ECOOP 2022)},
  pages =	{3:1--3:28},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-225-9},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{222},
  editor =	{Ali, Karim and Vitek, Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2022.3},
  URN =		{urn:nbn:de:0030-drops-162314},
  doi =		{10.4230/LIPIcs.ECOOP.2022.3},
  annote =	{Keywords: JavaScript, call graph construction, static program analysis}
}
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