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Validating the result of a Quantified Boolean Formula (QBF) solver: theory and practice
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Source Asia and South Pacific Design Automation Conference archive
Proceedings of the 2005 Asia and South Pacific Design Automation Conference table of contents
Shanghai, China
SESSION: Poster session II table of contents
Pages: 1047 - 1051  
Year of Publication: 2005
ISBN:0-7803-8737-6
Authors
Yinlei Yu  Princeton University Princeton, NJ
Sharad Malik  Princeton University Princeton, NJ
Sponsors
SIGDA: ACM Special Interest Group on Design Automation
: Shanghai IC Industry Association
: IEEE SSCS Shanghai Chapter
: IEEE CAS
: IEEE Beijing Section
: Fudan University
: Chinese Institute of Electronics
Publisher
ACM  New York, NY, USA
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ABSTRACT

Despite the increasing use of QBF solvers, current QBF solvers do not provide for any mechanism to verify their results. This paper demonstrates a methodology for independently validating the results of a DLL based QBF solver using the traces generated during the solving process. It also presents a mechanism to extract small unsatisfiable subformulas, called cores, from unsatisfiable QBF instances.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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QBF evaluation 2004 benchmarks, available from http://www.mrg.dist.unige.it/qbflib/benchmarks/04secondtestset.tar, 2004.
 
2
R. E. Bryant, S. K. Lahiri, and S. A. Seshia. Convergence testing in term-level bounded model checking. In Proc. CHARME'03, vol. 2860 of LNCS, pp. 348--362, 2003.
 
3
 
4
M. Cadoli and M. Schaerf. An algorithm to evaluate quantified Boolean formulae and its experimental evaluation. In Highlights of Satisfiability Research in 2000, 2000.
5
6
 
7
 
8
 
9
G. Gopalakrishnan, Y. Yang, and H. Sivaraj. QB or not QB: An efficient execution verification tool for memory orderings. In Proc. CAV'04, 2004.
 
10
 
11
M. Mneimneh and K. A. Sakallah. Computing vertex eccentricity in exponentially large graphs: QBF formulation and solution. In Proc. SAT'03, vol. 2919 of LNCS, pp. 411--425, 2003.
 
12
 
13
J. Rintanen. Constructing conditional plans by a theorem-prover. J. of Artificial Intelligence Research, 10:322--352, 1999.
14
 
15
Y. Yang, G. Gopalakrishnan, G. Lindstrom, and K. Slind. Analyzing the Intel Itanium memory ordering rules using logic programming and SAT. In Proc. CHARME'03, vol. 2860 of LNCS, pp. 81--95, 2003.
 
16
Y. Yu and S. Malik. yQuaffle QBF solver. available from http://www.princeton.edu/chaff/quaffle.html
 
17
L. Zhang and S. Malik. Conflict driven learning in a quantified Boolean satisfiability solver.
 
18
L. Zhang and S. Malik. Validating SAT solvers using an independent resolution-based checker: Practical implementations and other applications.
 
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