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Eventually Sound Points-To Analysis with Specifications

Authors Osbert Bastani, Rahul Sharma, Lazaro Clapp, Saswat Anand, Alex Aiken



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Author Details

Osbert Bastani
  • University of Pennsylvania, Philadelphia, USA
Rahul Sharma
  • Microsoft Research, Bangalore, India
Lazaro Clapp
  • Stanford University, USA
Saswat Anand
  • Stanford University, USA
Alex Aiken
  • Stanford University, USA

Acknowledgements

This work was supported by NSF grant CCF-1160904, and is also based on research sponsored by the Air Force Research Laboratory, under agreement number FA8750-12-2-0020. The U.S. Government is authorized to reproduce and distribute reprints for Governmental purposes notwithstanding any copyright notation thereon.

Cite AsGet BibTex

Osbert Bastani, Rahul Sharma, Lazaro Clapp, Saswat Anand, and Alex Aiken. Eventually Sound Points-To Analysis with Specifications. In 33rd European Conference on Object-Oriented Programming (ECOOP 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 134, pp. 11:1-11:28, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.ECOOP.2019.11

Abstract

Static analyses make the increasingly tenuous assumption that all source code is available for analysis; for example, large libraries often call into native code that cannot be analyzed. We propose a points-to analysis that initially makes optimistic assumptions about missing code, and then inserts runtime checks that report counterexamples to these assumptions that occur during execution. Our approach guarantees eventual soundness, which combines two guarantees: (i) the runtime checks are guaranteed to catch the first counterexample that occurs during any execution, in which case execution can be terminated to prevent harm, and (ii) only finitely many counterexamples ever occur, implying that the static analysis eventually becomes statically sound with respect to all remaining executions. We implement Optix, an eventually sound points-to analysis for Android apps, where the Android framework is missing. We show that the runtime checks added by Optix incur low overhead on real programs, and demonstrate how Optix improves a client information flow analysis for detecting Android malware.

Subject Classification

ACM Subject Classification
  • Theory of computation → Program analysis
Keywords
  • specification inference
  • static points-to analysis
  • runtime monitoring

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