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Documents authored by Chakraborty, Madhurima

Document
DOI: 10.4230/LIPIcs.ECOOP.2024.10
Indirection-Bounded Call Graph Analysis

Authors: Madhurima Chakraborty, Aakash Gnanakumar, Manu Sridharan, and Anders Møller

Published in: LIPIcs, Volume 313, 38th European Conference on Object-Oriented Programming (ECOOP 2024)

Abstract
Call graphs play a crucial role in analyzing the structure and behavior of programs. For JavaScript and other dynamically typed programming languages, static call graph analysis relies on approximating the possible flow of functions and objects, and producing usable call graphs for large, real-world programs remains challenging. In this paper, we propose a simple but effective technique that addresses performance issues encountered in call graph generation. We observe via a dynamic analysis that typical JavaScript program code exhibits small levels of indirection of object pointers and higher-order functions. We demonstrate that a widely used analysis algorithm, wave propagation, closely follows the levels of indirections, so that call edges discovered early are more likely to be true positives. By bounding the number of indirections covered by this analysis, in many cases it can find most true-positive call edges in less time. We also show that indirection-bounded analysis can similarly be incorporated into the field-based call graph analysis algorithm ACG. We have experimentally evaluated the modified wave propagation algorithm on 25 large Node.js-based JavaScript programs. Indirection-bounded analysis on average yields close to a 2X speed-up with only 5% reduction in recall and almost identical precision relative to the baseline analysis, using dynamically generated call graphs for the recall and precision measurements. To demonstrate the robustness of the approach, we also evaluated the modified ACG algorithm on 10 web-based and 4 mobile-based medium sized benchmarks, with similar results.
Cite as

Madhurima Chakraborty, Aakash Gnanakumar, Manu Sridharan, and Anders Møller. Indirection-Bounded Call Graph Analysis. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 10:1-10:22, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{chakraborty_et_al:LIPIcs.ECOOP.2024.10,
  author =	{Chakraborty, Madhurima and Gnanakumar, Aakash and Sridharan, Manu and M{\o}ller, Anders},
  title =	{{Indirection-Bounded Call Graph Analysis}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{10:1--10:22},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-341-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{313},
  editor =	{Aldrich, Jonathan and Salvaneschi, Guido},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2024.10},
  URN =		{urn:nbn:de:0030-drops-208599},
  doi =		{10.4230/LIPIcs.ECOOP.2024.10},
  annote =	{Keywords: JavaScript, call graphs, points-to analysis}
}
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.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.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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