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The Quest for Efficient Boolean Satisfiability Solvers
, 2002
"... has seen much interest in not just the theoretical computer science community, but also in areas where practical solutions to this problem enable significant practical applications. Since the first development of the basic search based algorithm proposed by Davis, Putnam, Logemann and Loveland (DPLL ..."
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has seen much interest in not just the theoretical computer science community, but also in areas where practical solutions to this problem enable significant practical applications. Since the first development of the basic search based algorithm proposed by Davis, Putnam, Logemann and Loveland (DPLL) about forty years ago, this area has seen active research effort with many interesting contributions that have culminated in stateoftheart SAT solvers today being able to handle problem instances with thousands, and in same cases even millions, of variables. In this paper we examine some of the main ideas along this passage that have led to our current capabilities. Given the depth of the literature in this field, it is impossible to do this in any comprehensive way; rather we focus on techniques with consistent demonstrated efficiency in available solvers. For the most part, we focus on techniques within the basic DPLL search framework, but also briefly describe other approaches and look at some possible future research directions. 1.
Propositional Satisfiability and Constraint Programming: a Comparative Survey
 ACM Computing Surveys
, 2006
"... Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research, crossfertilising occasionally. These two approaches to problem solving have a lot in common, as evidenced by similar ideas underlying the branch and prune algorithms ..."
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Cited by 34 (4 self)
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Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research, crossfertilising occasionally. These two approaches to problem solving have a lot in common, as evidenced by similar ideas underlying the branch and prune algorithms that are most successful at solving both kinds of problems. They also exhibit differences in the way they are used to state and solve problems, since SAT’s approach is in general a blackbox approach, while CP aims at being tunable and programmable. This survey overviews the two areas in a comparative way, emphasising the similarities and differences between the two and the points where we feel that one technology can benefit from ideas or experience acquired
SEARCHING FOR TRUTH: TECHNIQUES FOR SATISFIABILITY OF BOOLEAN FORMULAS
, 2003
"... I certify that I have read this thesis and that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy. ..."
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Cited by 9 (0 self)
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I certify that I have read this thesis and that in my opinion it is fully adequate, in scope and in quality, as a dissertation for the degree of Doctor of Philosophy.
MultiNode Static Logic Implications For Redundancy Identification
 PROC. DESIGN, AUTOMATION, AND TEST IN EUROPE CONF., 2000
, 2000
"... This paper presents a method for redundancy identification (RID) using multinode logic implications. The algorithm discovers a large number of direct and indirect implications by extending single node implications [7] to multiple nodes. The large number of implications found by multinode implicati ..."
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Cited by 6 (3 self)
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This paper presents a method for redundancy identification (RID) using multinode logic implications. The algorithm discovers a large number of direct and indirect implications by extending single node implications [7] to multiple nodes. The large number of implications found by multinode implication method introduces a new redundancy identification technique. Our approach uses an effective nodepair selection method which is O(n) in the number of nodes to reduce execution time, and it can be used as an efficient preprocessing phase for test generation. Application of these multinode static logic implications uncovered more redundancies in ISCAS85 combinational circuits than previous singlenode methods without excessive computational effort.
MultiNode Implications For Sequential Circuit Reachability Analysis And Redundancy Identification
"... OF THE THESIS MultiNode Implications for sequential circuit reachability analysis and redundancy identification by Kabir Gulrajani Thesis Director: Dr. Michael Hsiao In this thesis a method for using static logic implications for redunancy identification and state reachability analysis is prese ..."
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OF THE THESIS MultiNode Implications for sequential circuit reachability analysis and redundancy identification by Kabir Gulrajani Thesis Director: Dr. Michael Hsiao In this thesis a method for using static logic implications for redunancy identification and state reachability analysis is presented. It introduces a new time efficient way in which static learning information can be applied. The static learning procedure is extended to multiple nodes for obtaining more information, based on which more redundancies can be identified. The implication information is also used for identifying illegal pairs of flipflops in sequential circuits. Multinode implications greatly enhance the state reachability analysis procedure by finding illegal triplets. Although multinode implications can be used to find illegal states of any length we restrict this procedure to finding illegal triplets only. Finally, the illegal states found are used for finding sequentially untestable faults. On applying our methods to the ISCAS85 and ISCAS89 benchmark circuits, results indicate more untestable faults and illegal states are obtained when compared to singlenode implication method.
ABSTRACT Advances and Insights into Parallel SAT Solving
"... The recent improvements in SAT solving algorithms, driven by the quest to solve increasingly complex problem instances, has produced techniques whose objective is to prune large portions of the search space to converge quickly to a solution (for instance, conflictdriven learning). In particular, so ..."
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The recent improvements in SAT solving algorithms, driven by the quest to solve increasingly complex problem instances, has produced techniques whose objective is to prune large portions of the search space to converge quickly to a solution (for instance, conflictdriven learning). In particular, solutions have been suggested in this area which attack the problem by attempting to parallelize DPLLbased SAT. However, so far the results have been mixed, which, consequently, have led to a scarcity of research in this space. One of the challenges of this direction is that finding a good partitioning of the space is not straightforward when using a DPLLbased algorithm. Moreover, partitioning the problem limits the benefits that can be ripped from effective learning and good variable ordering heuristics in sequential solvers. In this paper, we propose techniques which improve upon previous approaches, primarily by improving the quality of learning during the search. Our first technique implements a parallel version of recursive learning (RL), which we use as a preprocessor to simplify the initial instance. Unlike previous DPLLbased approaches, RL can be easily partitioned and each processor learns information that is beneficial to solving the problem at hand. Our results indicate that this initial preprocessing can be done efficiently when divided among several processors, thereby boosting the performance of solving the resulting instance. In addition to RL, we explore strategies for improving parallel DPLLbased algorithms by adopting heuristics which have proven effective in the sequential domain, such as VSIDs, and by applying them to shared learning and partitioning. We show results that indicate improvement over previous work and reveal that future enhancement could lead to better mechanisms for pruning search space through shared learning strategies in a parallel framework. 1.
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"... One of the goals of 18760 is that you acquire enough about the “fundamental ” ideas of CAD algorithms to be able to read new papers and see where they borrow from known techniques, and where they innovate. Even just this far through this class, you (should) now know a lot about basic Boolean repres ..."
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One of the goals of 18760 is that you acquire enough about the “fundamental ” ideas of CAD algorithms to be able to read new papers and see where they borrow from known techniques, and where they innovate. Even just this far through this class, you (should) now know a lot about basic Boolean representation, manipulation, verification, etc. The intent here is for you to write a short review (not to exceed 4 typed 8.5 X 11 pages, in a reasonable font, including any figures and tables) analyzing the attached paper: