2 Search Results for "Ruiz, Daniel"

Document
DOI: 10.4230/LIPIcs.ECOOP.2022.9
A Deterministic Memory Allocator for Dynamic Symbolic Execution

Authors: Daniel Schemmel, Julian Büning, Frank Busse, Martin Nowack, and Cristian Cadar

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

Abstract
Dynamic symbolic execution (DSE) has established itself as an effective testing and analysis technique. While the memory model in DSE has attracted significant attention, the memory allocator has been largely ignored, despite its significant influence on DSE. In this paper, we discuss the different ways in which the memory allocator can influence DSE and the main design principles that a memory allocator for DSE needs to follow: support for external calls, cross-run and cross-path determinism, spatially and temporally distanced allocations, and stability. We then present KDAlloc, a deterministic allocator for DSE that is guided by these six design principles. We implement KDAlloc in KLEE, a popular DSE engine, and first show that it is competitive with KLEE’s default allocator in terms of performance and memory overhead, and in fact significantly improves performance in several cases. We then highlight its benefits for use-after-free error detection and two distinct DSE-based techniques: MoKlee, a system for saving DSE runs to disk and later (partially) restoring them, and SymLive, a system for finding infinite-loop bugs.
Cite as

Daniel Schemmel, Julian Büning, Frank Busse, Martin Nowack, and Cristian Cadar. A Deterministic Memory Allocator for Dynamic Symbolic Execution. In 36th European Conference on Object-Oriented Programming (ECOOP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 222, pp. 9:1-9:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

Copy BibTex To Clipboard

@InProceedings{schemmel_et_al:LIPIcs.ECOOP.2022.9,
  author =	{Schemmel, Daniel and B\"{u}ning, Julian and Busse, Frank and Nowack, Martin and Cadar, Cristian},
  title =	{{A Deterministic Memory Allocator for Dynamic Symbolic Execution}},
  booktitle =	{36th European Conference on Object-Oriented Programming (ECOOP 2022)},
  pages =	{9:1--9:26},
  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.2022.9},
  URN =		{urn:nbn:de:0030-drops-162372},
  doi =		{10.4230/LIPIcs.ECOOP.2022.9},
  annote =	{Keywords: memory allocation, dynamic symbolic execution}
}
Document
DOI: 10.4230/DagSemProc.07071.4
A Fast Algorithm for Matrix Balancing

Authors: Philip A. Knight and Daniel Ruiz

Published in: Dagstuhl Seminar Proceedings, Volume 7071, Web Information Retrieval and Linear Algebra Algorithms (2007)

Abstract
As long as a square nonnegative matrix A contains sufficient nonzero elements, then the matrix can be balanced, that is we can find a diagonal scaling of A that is doubly stochastic. A number of algorithms have been proposed to achieve the balancing, the most well known of these being the Sinkhorn-Knopp algorithm. In this paper we derive new algorithms based on inner-outer iteration schemes. We show that the Sinkhorn-Knopp algorithm belongs to this family, but other members can converge much more quickly. In particular, we show that while stationary iterative methods offer little or no improvement in many cases, a scheme using a preconditioned conjugate gradient method as the inner iteration can give quadratic convergence at low cost.
Cite as

Philip A. Knight and Daniel Ruiz. A Fast Algorithm for Matrix Balancing. In Web Information Retrieval and Linear Algebra Algorithms. Dagstuhl Seminar Proceedings, Volume 7071, pp. 1-18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

Copy BibTex To Clipboard

@InProceedings{knight_et_al:DagSemProc.07071.4,
  author =	{Knight, Philip A. and Ruiz, Daniel},
  title =	{{A Fast Algorithm for Matrix Balancing}},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  pages =	{1--18},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7071},
  editor =	{Andreas Frommer and Michael W. Mahoney and Daniel B. Szyld},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07071.4},
  URN =		{urn:nbn:de:0030-drops-10735},
  doi =		{10.4230/DagSemProc.07071.4},
  annote =	{Keywords: Matrix balancing, Sinkhorn-Knopp algorithm, doubly stochastic matrix, conjugate gradient iteration}
}
  • Refine by Author
  • 1 Busse, Frank
  • 1 Büning, Julian
  • 1 Cadar, Cristian
  • 1 Knight, Philip A.
  • 1 Nowack, Martin
  • Show More...

  • Refine by Classification
  • 1 Software and its engineering → Software testing and debugging

  • Refine by Keyword
  • 1 Matrix balancing
  • 1 Sinkhorn-Knopp algorithm
  • 1 conjugate gradient iteration
  • 1 doubly stochastic matrix
  • 1 dynamic symbolic execution
  • Show More...

  • Refine by Type
  • 2 document

  • Refine by Publication Year
  • 1 2007
  • 1 2022

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail
© 2023-2024 Schloss Dagstuhl – LZI GmbH Imprint Privacy Contact