
Theory and Applications of Satisfiability Testing -- SAT 2015
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Content
- Intro
- Preface
- Organization
- Pragmatic Approach to Formal Verification
- Applying Satisfiability to the Analysisof Cryptography
- Random Formulas are Irrelevant, Right?
- Contents
- CCAnr: A Configuration Checking Based Local Search Solver for Non-random Satisfiability
- 1 Introduction
- 2 Solver Description
- 2.1 The CCA Heuristic and Swcca
- 2.2 The CCAnr Algorithm
- 2.3 Implementation Details
- 3 Experimental Results
- References
- PBLib -- A Library for Encoding Pseudo-Boolean Constraints into CNF
- 1 Introduction
- 2 Pseudo-Boolean Constraints and Encodings
- 3 Description of the PBLib
- 3.1 Components of the PBLib
- 3.2 Example
- 4 Included Tools
- 5 Empirical Evaluation and Related Work
- 6 Conclusion
- References
- Speeding up MUS Extraction with Preprocessing and Chunking
- 1 Introduction
- 2 Preliminaries
- 3 LMUS Extraction
- 4 Chunking
- 5 Experiments
- 5.1 Overall GMUS Evaluation
- 5.2 Parameter Impact
- 6 Conclusions
- References
- Improved Algorithms for Sparse MAX-SAT and MAX-k-CSP
- 1 Introduction
- 1.1 Related Work
- 1.2 Organization of the Paper
- 2 Preliminaries
- 2.1 MAXSAT, MAX-k-SAT, MAX-k-CSP
- 2.2 Concentration Bounds
- 3 MAX-k-CSP
- 3.1 Known Algorithms for MAX-2-CSP
- 3.2 A Polynomial-space Algorithm for MAX-k-CSP
- 3.3 An Exponential-Space Algorithm for MAX-k-CSP
- 4 MAX-SAT and MAX-k-SAT
- 4.1 A Polynomial-Space Algorithm for MAX-SAT
- 4.2 An Exponential-Space Algorithm for MAX-SAT
- 5 Sparse Depth-2 Threshold Circuits
- 6 Open Questions
- References
- Laissez-Faire Caching for Parallel #SAT Solving
- 1 Introduction
- 2 Basic Notations
- 3 #SAT Solving
- 3.1 Conflict Learning
- 3.2 Sub-Formula Decomposition
- 3.3 Formula Caching
- 3.4 Incorrect Results in the Cache
- 4 Laissez-Faire Caching
- 4.1 Node Re-Computation
- 4.2 Memory Consumption and Cleanup
- 5 countAntom Solver Structure
- 5.1 Node Computation
- 5.2 Node Order
- 5.3 Caching
- 6 Experimental Results
- 6.1 Benchmarks
- 6.2 Parallel Performance
- 6.3 Impact of Laissez-Faire Caching
- 7 Conclusion
- References
- SATGraf: Visualizing the Evolution of SAT Formula Structure in Solvers
- 1 Introduction
- 2 How SATGraf Works
- 3 Results
- 3.1 Observation #1: VSIDS Chooses High-Centrality Bridge Variables
- 3.2 Observation #2: VSIDS Moves Infrequently Between Communities
- 3.3 Observation #3: Backtracking May Incur Unnecessary Overhead
- 4 Related Work
- 5 Conclusion
- References
- Hints Revealed
- 1 Introduction
- 2 Preliminaries
- 3 Hint Addition
- 4 Hint Creation Algorithms
- 4.1 Avoiding Failing Branches
- 4.2 Randomized Hints
- 5 Theoretical Basis
- 6 Experimental Results
- 6.1 AFB Results: SAT 2013
- 6.2 AFB Results: SAT 2014
- 6.3 RH Results: SAT 2013
- 7 Discussion
- References
- Mining Backbone Literals in Incremental SAT
- 1 Introduction
- 2 Mining Backbone Literals
- 2.1 Optimizations and Implementation Details
- 2.2 Constants can Increase the Number of Assumptions
- 3 A Case Study: Using MBL in the Context of MUC Extraction
- 3.1 How HaifaMUC Extracts Minimal Unsatisfiable Cores
- 3.2 Experiments
- 3.3 Mitigating the Side-Effect of Assumptions on MUC Search
- 4 Conclusions and Future Work
- References
- Constructing SAT Filters with a Quantum Annealer
- 1 Introduction
- 2 Filters, SAT Filters and Blocked SAT Filters
- 2.1 SAT Filters
- 2.2 Blocked SAT Filters
- 3 Solving CSPs in the Ising Model with a D-Wave Processor
- 3.1 Constraint Satisfaction Problems in the Ising Model
- 3.2 Graph Minors in the Ising Model
- 4 SAT Variants in the Ising Model
- 4.1 NAE3SAT
- Monotone NAE3SAT.
- 4.2 MAX-CUT SAT Variants
- 4.3 Bipartite 4FLSAT
- 4.4 Threshold Analysis
- 4.5 Software Solvers
- 5 Case Study 1: A Blocked MNAE3SAT Filter
- 6 Case Study 2: Filter and Performance Scaling
- 6.1 Scaling of Solution Time
- 7 Conclusions
- References
- #SAT: Projected Model Counting
- 1 Introduction
- 2 Preliminaries
- 3 Model Counting
- 3.1 Solution Enumeration Using SAT Solvers
- 3.2 DPLL-style Model Counting
- 4 Projected Model Counting
- 4.1 Restricting Search to Priority Variables
- 4.2 Blocking Seen Solutions
- 4.3 Counting Models of Projected d-DNNF
- 5 Experiments
- 5.1 Uniform Random 3-SAT and Boolean Circuits
- 5.2 Planning
- 6 Related Work and Conclusion
- References
- Computing Maximal Autarkies with Few and Simple Oracle Queries
- 1 Introduction
- 2 Preliminaries
- 3 Oracles
- 4 The Basic Translation
- 4.1 Basic Usages
- 4.2 Adding Positive ``Steering'' Clauses
- 5 The New Algorithm
- 6 Conclusion and Outlook
- References
- HordeSat: A Massively Parallel Portfolio SAT Solver
- 1 Introduction
- 2 Preliminaries
- 3 Related Work
- 4 Design Decisions
- 5 Black Box for Portfolios
- 6 The Portfolio Algorithm
- 6.1 Diversification
- 6.2 Clause Sharing
- 7 Experimental Evaluation
- 7.1 Clause Sharing and Diversification
- 7.2 Scaling on Application Benchmarks
- 7.3 Comparison with Plingeling
- 8 Conclusion
- 8.1 Future Work
- References
- Preprocessing for DQBF
- 1 Introduction
- 2 Preliminaries
- 3 Incomplete, but Cheap Decision Procedures
- 4 Preprocessing Techniques for DQBF
- 4.1 Backbones, Monotonic and Equivalent Variables
- 4.2 Reduction of Dependency Sets
- 4.3 Universal Reduction, Resolution, and Universal Expansion
- 4.4 Blocked Clause Elimination
- 4.5 Structure Extraction
- 5 Experimental Results
- 6 Conclusion
- References
- Incrementally Computing Minimal Unsatisfiable Cores of QBFs via a Clause Group Solver API
- 1 Introduction
- 2 Implementing a Clause Group API
- 3 Computing Minimal Unsatisfiable Cores of QBFs
- 4 Conclusion
- References
- On Compiling CNFs into Structured Deterministic DNNFs
- 1 Introduction
- 2 Preliminaries
- 3 From Dynamic Programming to Structured d-DNNFs
- 3.1 Branch Decompositions, Projections, and PS-width
- 3.2 Records and Dynamic Programming
- 3.3 Constructing a Structured d-DNNF
- 4 Corollaries
- 5 A Lower Bound for Clique-Width
- 6 Conclusion
- References
- SpySMAC: Automated Configuration and Performance Analysis of SAT Solvers
- 1 Introduction
- 2 Algorithm Configuration and Analysis
- 3 SpySMAC's Framework
- 4 Spying on Lingeling and probSAT
- 5 Conclusion
- References
- Community Structure Inspired Algorithms for SAT and #SAT
- 1 Introduction
- 2 Preliminaries
- 2.1 SAT and #SAT
- 2.2 Parameterized Complexity
- 2.3 Hitting Formulas
- 2.4 Treewidth
- 3 h-Communities and h-Modularity
- 4 Finding h-Structures
- 5 Using h-Structures
- 6 Concluding Notes
- References
- Using Community Structure to Detect Relevant Learnt Clauses
- 1 Introduction
- 2 Preliminaries
- 3 Clause Learning Destroys the Community Structure
- 4 On the Relevance of Learnt Clauses
- 5 Detecting Relevant Learnt Clauses
- 6 Experimental Evaluation
- 7 Related Work
- 8 Conclusions and Future Work
- References
- Recognition of Nested Gates in CNF Formulas
- 1 Introduction
- 1.1 Related Work
- 1.2 Contributions
- 2 Theoretical Background
- 2.1 Gates and Monotonicity
- 2.2 And-Inverter Graphs (AIG)
- 2.3 Preprocessing
- 3 Recognition of Nested Gates
- 3.1 Iterative Root Selection
- 3.2 Recursive Gate Extraction
- 3.3 Equivalence Detection Methods
- 3.4 AIG Construction
- 4 Experimental Results
- 4.1 Equivalence Detection Methods
- 4.2 Preprocessing and Gate Recognition
- 4.3 Maximum Number of Recognition Tries
- 4.4 And-Inverter Graphs
- 5 Conclusion and Future Work
- References
- Exploiting Resolution-Based Representations for MaxSAT Solving
- 1 Introduction
- 2 Preliminaries
- 3 Graph Representations
- 4 New Partition-Based Algorithm for MaxSAT
- 4.1 Algorithm Description
- 4.2 Partition and Merge of Soft Clauses
- 4.3 Algorithm Analysis
- 5 Experimental Results
- 6 Conclusions and Future Work
- References
- SAT-Based Formula Simplification
- 1 Introduction
- 2 Preliminaries
- 3 Formula Simplification with SAT
- 3.1 Prime Implicant/Implicate Enumeration
- 3.2 Computing a Smallest Prime Cover
- 4 Preliminary Results
- 4.1 PLA Benchmarks
- 4.2 Bi-decomposition Interpolation Benchmarks
- 4.3 Quasigroup Classification Benchmarks
- 5 Conclusions
- References
- Volt: A Lazy Grounding Framework for Solving Very Large MaxSAT Instances
- 1 Introduction
- 2 Volt: A Lazy Grounding Framework
- 3 Empirical Evaluation
- 4 Conclusion
- References
- Between SAT and UNSAT: The Fundamental Difference in CDCL SAT
- 1 Introduction
- 2 Background
- 2.1 COMiniSatPS
- 2.2 VSIDS Branching Heuristic
- 2.3 Learned Clause Management
- 2.4 Restart Strategies
- 3 The SAT/UNSAT Difference of CDCL in Practice
- 3.1 Roles of Learned Clauses
- 3.2 Effects of Restarts
- 3.3 VSIDS and Variable Decay Factor
- 4 Refining the Hybrid Strategy
- 5 Conclusion
- References
- Efficient MUS Enumeration of Horn Formulae with Applications to Axiom Pinpointing
- 1 Introduction
- 2 Preliminaries
- 3 MUS Enumeration in Horn Formulae
- 4 Algorithm for Group-MUS Enumeration in Horn Formulae
- 4.1 Organization
- 4.2 Computing Maximal Models
- 4.3 Adding Blocking Clauses
- 4.4 Deciding Satisfiability of Horn Formulae
- 4.5 MUS Extraction in Horn Formulae
- 5 Comparison with Existing Alternatives
- 5.1 EL+SAT
- 5.2 EL2MCS
- 5.3 SATPin
- 6 Experimental Results
- 6.1 Experimental Setup
- 6.2 COI Instances
- 6.3 x2 Instances
- 6.4 Assessment of Non SAT-Based Axiom Pinpointing Tools
- 7 Conclusions and Future Work
- References
- QELL: QBF Reasoning with Extended Clause Learning and Levelized SAT Solving
- 1 Introduction
- 2 Preliminaries
- 3 Algorithmic Flow
- 4 Learning
- 4.1 Solution Learning by Levelized Blocking
- 4.2 Solution Learning in the Presence of Circuit Information
- 4.3 Conflict Learning
- 5 Related Work
- 6 Experimental Results
- 7 Conclusion and Future Work
- References
- SMT-RAT: An Open Source C++ Toolbox for Strategic and Parallel SMT Solving
- 1 Introduction
- 2 System Architecture
- 2.1 Data Structures and Basic Procedures: CArL carl
- 2.2 Interfaces and Strategic Compositions of Procedures: SMT-RAT smtrathtml
- 3 Experimental Results and Future Work
- References
- Search-Space Partitioning for Parallelizing SMT Solvers
- 1 Introduction
- 2 Preliminaries
- 3 Parallelization Approaches for SMT
- 3.1 Search-Space Partitioning in SMT
- 3.2 Combining Search Space Partitioning and Portfolio
- 4 A Cloud-Based Parallel SMT Solver for QF_UF
- 4.1 Partitioning Heuristics
- 4.2 The Client-Server Architecture
- 5 Experimental Results
- 5.1 Comparing the Implementation to the Portfolio Approach
- 5.2 Comparing the Partitioning Heuristics
- 5.3 Comparison to Other SMT Solvers
- 6 Conclusions
- References
- A New Approach to Partial MUS Enumeration
- 1 Introduction
- 2 Preliminaries
- 3 Related Work and the MARCO Algorithm
- 3.1 The MARCO Algorithm
- 4 A First Extension: Determine MUS Members via Map
- 5 Using Blocks to Speed-Up Partial MUS Enumeration
- 5.1 Determine the Blocks
- 5.2 Proving the Block Property
- 5.3 Using Block Information During shrink-Method
- 5.4 Using Block Information to Find More MCSes
- 6 Practical Results
- 6.1 Workload Computation
- 7 Conclusion
- References
- Evaluating CDCL Variable Scoring Schemes
- 1 Introduction
- 2 Decision Heuristics
- 3 Implementation
- 3.1 Fast Queue for VMTF
- 3.2 Generic Queue for all Decision Heuristics
- 3.3 Rescore, Reuse-Trail and Complexity
- 4 Results
- 5 Conclusion
- References
- SAT-Based Horn Least Upper Bounds
- 1 Introduction
- 2 Preliminaries
- 3 SAT-Based Algorithms
- 3.1 HFLUBBER: An Iterative Refinement Approach
- 3.2 IP-HORN: Computing all Horn Prime Implicates
- 3.3 Discussion
- 4 Results
- 5 Conclusions
- References
- Author Index
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