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DOI: 10.4230/LIPIcs.ECOOP.2024.36

Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report

Authors: Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden

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

Abstract

Interprocedural data-flow analysis is important for computing precise information on whole programs. In theory, the popular algorithmic framework interprocedural distributive environments (IDE) provides a tool to solve distributive interprocedural data-flow problems efficiently. Yet, unfortunately, available state-of-the-art implementations of the IDE framework start to run into scalability issues for programs with several thousands of lines of code, depending on the static analysis domain. Since the IDE framework is a basic building block for many static program analyses, this presents a serious limitation. In this paper, we report on our experience with making the IDE algorithm scale to C/C++ applications with up to 500 000 lines of code. We analyze the IDE algorithm and its state-of-the-art implementations to identify their weaknesses related to scalability at both a conceptual and implementation level. Based on this analysis, we propose several optimizations to overcome these weaknesses, aiming at a sweet spot between reducing running time and memory consumption. As a result, we provide an improved IDE solver that implements our optimizations within the PhASAR static analysis framework. Our evaluation on real-world C/C++ applications shows that applying the optimizations speeds up the analysis on average by up to 7×, while also reducing memory consumption by 7× on average as well. For the first time, these optimizations allow us to analyze programs with several hundreds of thousands of lines of LLVM-IR code in reasonable time and space.

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Fabian Schiebel, Florian Sattler, Philipp Dominik Schubert, Sven Apel, and Eric Bodden. Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report. In 38th European Conference on Object-Oriented Programming (ECOOP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 313, pp. 36:1-36:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{schiebel_et_al:LIPIcs.ECOOP.2024.36,
  author =	{Schiebel, Fabian and Sattler, Florian and Schubert, Philipp Dominik and Apel, Sven and Bodden, Eric},
  title =	{{Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report}},
  booktitle =	{38th European Conference on Object-Oriented Programming (ECOOP 2024)},
  pages =	{36:1--36:28},
  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.2024.36},
  URN =		{urn:nbn:de:0030-drops-208859},
  doi =		{10.4230/LIPIcs.ECOOP.2024.36},
  annote =	{Keywords: Interprocedural data-flow analysis, IDE, LLVM, C/C++}
}

Document

DOI: 10.4230/LIPIcs.ECOOP.2021.2

Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis

Authors: Philipp Dominik Schubert, Ben Hermann, and Eric Bodden

Published in: LIPIcs, Volume 194, 35th European Conference on Object-Oriented Programming (ECOOP 2021)

Abstract

Static analysis is used to automatically detect bugs and security breaches, and aids compiler optimization. Whole-program analysis (WPA) can yield high precision, however causes long analysis times and thus does not match common software-development workflows, making it often impractical to use for large, real-world applications. This paper thus presents the design and implementation of ModAlyzer, a novel static-analysis approach that aims at accelerating whole-program analysis by making the analysis modular and compositional. It shows how to compute lossless, persisted summaries for callgraph, points-to and data-flow information, and it reports under which circumstances this function-level compositional analysis outperforms WPA. We implemented ModAlyzer as an extension to LLVM and PhASAR, and applied it to 12 real-world C and C++ applications. At analysis time, ModAlyzer modularly and losslessly summarizes the analysis effect of the library code those applications share, hence avoiding its repeated re-analysis. The experimental results show that the reuse of these summaries can save, on average, 72% of analysis time over WPA. Moreover, because it is lossless, the module-wise analysis fully retains precision and recall. Surprisingly, as our results show, it sometimes even yields precision superior to WPA. The initial summary generation, on average, takes about 3.67 times as long as WPA.

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Philipp Dominik Schubert, Ben Hermann, and Eric Bodden. Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis. In 35th European Conference on Object-Oriented Programming (ECOOP 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 194, pp. 2:1-2:31, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{schubert_et_al:LIPIcs.ECOOP.2021.2,
  author =	{Schubert, Philipp Dominik and Hermann, Ben and Bodden, Eric},
  title =	{{Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis}},
  booktitle =	{35th European Conference on Object-Oriented Programming (ECOOP 2021)},
  pages =	{2:1--2:31},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-190-0},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{194},
  editor =	{M{\o}ller, Anders and Sridharan, Manu},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2021.2},
  URN =		{urn:nbn:de:0030-drops-140453},
  doi =		{10.4230/LIPIcs.ECOOP.2021.2},
  annote =	{Keywords: Inter-procedural static analysis, compositional analysis, LLVM, C/C++}
}

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Scaling Interprocedural Static Data-Flow Analysis to Large C/C++ Applications: An Experience Report

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Lossless, Persisted Summarization of Static Callgraph, Points-To and Data-Flow Analysis

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