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Documents authored by Nguyen Quang Do, Lisa


Document
Front Matter
Front Matter, Table of Contents, Preface, Conference Organization

Authors: Lisa Nguyen Quang Do and Manuel Rigger

Published in: DARTS, Volume 6, Issue 2, Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020)


Abstract
Front Matter, Table of Contents, Preface, Conference Organization

Cite as

Special Issue of the 34th European Conference on Object-Oriented Programming (ECOOP 2020). Dagstuhl Artifacts Series (DARTS), Volume 6, Issue 2, pp. 0:i-0:xii, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@Article{nguyenquangdo_et_al:DARTS.6.2.0,
  author =	{Nguyen Quang Do, Lisa and Rigger, Manuel},
  title =	{{Front Matter, Table of Contents, Preface, Conference Organization}},
  pages =	{0:i--0:xii},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2020},
  volume =	{6},
  number =	{2},
  editor =	{Nguyen Quang Do, Lisa and Rigger, Manuel},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.6.2.0},
  URN =		{urn:nbn:de:0030-drops-131977},
  doi =		{10.4230/DARTS.6.2.0},
  annote =	{Keywords: Front Matter, Table of Contents, Preface, Conference Organization}
}
Document
Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java

Authors: Johannes Späth, Lisa Nguyen Quang Do, Karim Ali, and Eric Bodden

Published in: LIPIcs, Volume 56, 30th European Conference on Object-Oriented Programming (ECOOP 2016)


Abstract
Many current program analyses require highly precise pointer information about small, tar- geted parts of a given program. This motivates the need for demand-driven pointer analyses that compute information only where required. Pointer analyses generally compute points-to sets of program variables or answer boolean alias queries. However, many client analyses require richer pointer information. For example, taint and typestate analyses often need to know the set of all aliases of a given variable under a certain calling context. With most current pointer analyses, clients must compute such information through repeated points-to or alias queries, increasing complexity and computation time for them. This paper presents Boomerang, a demand-driven, flow-, field-, and context-sensitive pointer analysis for Java programs. Boomerang computes rich results that include both the possible allocation sites of a given pointer (points-to information) and all pointers that can point to those allocation sites (alias information). For increased precision and scalability, clients can query Boomerang with respect to particular calling contexts of interest. Our experiments show that Boomerang is more precise than existing demand-driven pointer analyses. Additionally, using Boomerang, the taint analysis FlowDroid issues up to 29.4x fewer pointer queries compared to using other pointer analyses that return simpler pointer infor- mation. Furthermore, the search space of Boomerang can be significantly reduced by requesting calling contexts from the client analysis.

Cite as

Johannes Späth, Lisa Nguyen Quang Do, Karim Ali, and Eric Bodden. Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java. In 30th European Conference on Object-Oriented Programming (ECOOP 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 56, pp. 22:1-22:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{spath_et_al:LIPIcs.ECOOP.2016.22,
  author =	{Sp\"{a}th, Johannes and Nguyen Quang Do, Lisa and Ali, Karim and Bodden, Eric},
  title =	{{Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java}},
  booktitle =	{30th European Conference on Object-Oriented Programming (ECOOP 2016)},
  pages =	{22:1--22:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-014-9},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{56},
  editor =	{Krishnamurthi, Shriram and Lerner, Benjamin S.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2016.22},
  URN =		{urn:nbn:de:0030-drops-61164},
  doi =		{10.4230/LIPIcs.ECOOP.2016.22},
  annote =	{Keywords: Demand-Driven; Static Analysis; IFDS; Aliasing; Points-to Analysis}
}
Document
Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java (Artifact)

Authors: Johannes Späth, Lisa Nguyen Quang Do, Karim Ali, and Eric Bodden

Published in: DARTS, Volume 2, Issue 1, Special Issue of the 30th European Conference on Object-Oriented Programming (ECOOP 2016)


Abstract
Evaluating pointer analyses with respect to soundness and precision has been a tedious task. Within this artifact we present PointerBench, the benchmark suite used in the paper to compare the pointer analysis Boomerang with two other demand-driven pointer analyses, SB [Sridharan and Bodik, 2006] and DA [Yan et al., 2011]. We show PointerBench can be used to test different pointer analyses. In addition to that, the artifact contains usage examples for Boomerang on simple test programs. The test programs and the input on these programs to Boomerang can be changed to experiment with the algorithm and its features. Additionally, the artifact contains the integration of Boomerang, SB, and DA into FlowDroid, which can then be executed on arbitrary Android applications.

Cite as

Johannes Späth, Lisa Nguyen Quang Do, Karim Ali, and Eric Bodden. Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java (Artifact). In Special Issue of the 30th European Conference on Object-Oriented Programming (ECOOP 2016). Dagstuhl Artifacts Series (DARTS), Volume 2, Issue 1, pp. 12:1-12:2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@Article{spath_et_al:DARTS.2.1.12,
  author =	{Sp\"{a}th, Johannes and Nguyen Quang Do, Lisa and Ali, Karim and Bodden, Eric},
  title =	{{Boomerang: Demand-Driven Flow- and Context-Sensitive Pointer Analysis for Java (Artifact)}},
  pages =	{12:1--12:2},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2016},
  volume =	{2},
  number =	{1},
  editor =	{Sp\"{a}th, Johannes and Nguyen Quang Do, Lisa and Ali, Karim and Bodden, Eric},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DARTS.2.1.12},
  URN =		{urn:nbn:de:0030-drops-61334},
  doi =		{10.4230/DARTS.2.1.12},
  annote =	{Keywords: Demand-Driven; Static Analysis; IFDS; Aliasing; Points-to Analysis}
}
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