6254649
Disjunctive Image Computation for Embedded Software Verification
Finite state models generated from software programs have unique characteristics that are not exploited by existing model checking algorithms. In this paper, we propose a novel disjunctive image computation algorithm and other simplifications based on these characteristics. Our algorithm divides an image computation into a disjunctive set of easier ones that can be performed in isolation. Hypergraph partitioning is used to minimize the number of live variables in each disjunctive component. We use the live variables to simplify transition relations and reachable state subsets. Our experiments on a set of real-world C programs show that the new algorithm achieves orders-of-magnitude performance improvement over the best known conjunctive image computation algorithm
15353920
Beyond safety: customized SAT-based model checking
Model checking of safety properties has taken a significant lead over nonsafety properties in recent years. To bridge the gap, we propose dedicated SAT-based model checking algorithms for properties beyond safety. Previous bounded model checking (BMC) approaches have relied on either converting such properties to safety checking, or finding proofs by deriving termination criteria using loop-free path analysis. Instead, our approach uses a customized SAT-based formulation for bounded model checking of nonsafety properties, and determines the completeness bounds for liveness using unbounded SAT-based analysis. Our main contributions are: 1) Customized property translations for LTL formulas for BMC, with novel features that utilize partitioning, learning, and incremental formulation. Customized translations not only improve the BMC performance significantly in comparison to standard monolithic LTL translations, but also allow efficient derivation and use of completeness bounds. Though we discuss the translation schemas for liveness, they can be easily extended to handle other LTL properties as well. 2) Customized formulations for determining completeness bounds for liveness using SAT-based unbounded model checking (UMC) rather than using loop-free path analysis. These formulations comprise greatest fixed-point and least fixed-point computations to efficiently handle nested properties using SAT-based quantification approaches. We show the effectiveness of our overall approach for checking liveness on public benchmarks and several industry designs.
600527
Learning from BDDs in SAT-based bounded model checking
Bounded Model Checking (BMC) based on Boolean Satisfiability (SAT) procedures has recently gained popularity as an alternative to BDD-based model checking techniques for finding bugs in large designs. In this paper, we explore the use of learning from BDDs, where learned clauses generated by BDD-based analysis are added to the SAT solver, to supplement its other learning mechanisms. We propose several heuristics for guiding this process, aimed at increasing the usefulness of the learned clauses, while reducing the overheads. We demonstrate the effectiveness of our approach on several industrial designs, where BMC performance is improved and the design can be searched up to a greater depth by use of BDD-based learning.
11387042
Predicate learning and selective theory deduction for a difference logic solver
Design and verification of systems at the register-transfer (RT) or behavioral level require the ability to reason at higher levels of abstraction. Difference logic consists of an arbitrary Boolean combination of propositional variables and difference predicates and therefore provides an appropriate abstraction. In this paper, we present several new optimization techniques for efficiently deciding difference logic formulas. We use the lazy approach by combining a DPLL Boolean SAT procedure with a dedicated graph-based theory solver, which adds transitivity constraints among difference predicates on a "need-to" basis. Our new optimization techniques include flexible theory constraint propagation, selective theory deduction, and dynamic predicate learning. We have implemented these techniques in our lazy solver. We demonstrate the effectiveness of the proposed techniques on public benchmarks through a set of controlled experiments
8665183
Dynamic detection and removal of inactive clauses in SAT with application in image computation
In this paper, we present a new technique for the efficient dynamic detection and removal of inactive clauses, i.e. clauses that do not affect the solutions of interest of a Boolean satisfiability (SAT) problem. The algorithm is based on the extraction of gate connectivity information during generation of the Boolean formula from the circuit, and its use in the inner loop of a branch-and-bound SAT algorithm. The motivation for this optimization is to exploit the circuit structure information, which can be used to find unobservable gates at circuit outputs under dynamic conditions. It has the potential to speed up all applications of SAT in which the SAT formula is derived from a logic circuit. In particular, we find that it has considerable impact on an image computation algorithm based on SAT. We present practical results for benchmark circuits which show that the use of this optimization consistently improves the performance for reachability analysis, in some cases enabling the prototype tool to reach more states than otherwise possible.
10395010
Abstraction and BDDs Complement SAT-Based BMC in DiVer
Bounded Model Checking (BMC) based on Boolean Satisfiability (SAT) procedures has recently gained popularity for finding bugs in large designs. However, due to its incompleteness, there is a need to perform deeper searches for counterexamples, or a proof by induction where possible. The DiVer verification platform uses abstraction and BDDs to complement BMC in the quest for completeness. We demonstrate the effectiveness of our approach in practice on industrial designs.
14666453
An Interpolated Volume Data Model
Publisher Summary This chapter explores the basic functionality of the volume data model. It considers examples from biology and volumes of measurement from quantum physics. The data model is similar in the two cases, but the operations that are commonly used are quite different. In the second case, for instance, one is often interested in conditions on the behavior of local differential operators, such as zero-flow surfaces, while in the biological case one has a mix of value conditions and geometric condition. With these two application fields, this chapter highlights the generality and flexibility of the model. The system is based on a commercial database, augmented with specialized functions to manipulate the volume data model. The chapter demonstrates various operations specifying queries both using a graphical user interface and entering them directly in structured query language (SQL) augmented with the volume algebra operations.
37922436
Improved Bandwidth Approximation for Trees and Chordal Graphs
A linear arrangement of an n-vertex graph G=(V,E) is a one?one mapping f of the vertex set V onto the set n]={0,1,?,n?1}. The bandwidth of this linear arrangement is the maximum difference between the images of the endpoints of any edge in E(G). When the input graph G is a tree, the best known approximation algorithms for the minimum bandwidth linear arrangement (which are based on the principle of volume respecting embeddings) output a linear arrangement which has bandwidth within O(log3n) of the optimal bandwidth. In this paper, we present a simple randomized O(log2.5n)-approximation algorithm for bandwidth minimization on trees. We also show that a close variant of this algorithm gives a similar performance guarantee for chordal graphs.
7444548
A wavelet data model for image databases
This paper defines wavelet transforms as a datatype suitable for inclusion in databases and an algebra for the manipulation of this data type.
14357490
A Distributed Self-Stabilizing Algorithm for Finding a Connected Dominating Set in a Graph
A connected dominating set of a graph G is a set of nodes of G such that every node in G is either in the set or is adjacent to some node in the set, and the graph induced by the elements of the set is connected. Connected dominating sets have major applications in routing in wireless ad-hoc networks. In this paper, we present a distributed self-stabilizing algorithm for finding a connected dominating set of a graph. Starting from an arbitrary initial state, the algorithm finds a connected dominating set in O(N^2) time, where N is the number of nodes. We also show detailed simulation results to indicate that in practice, the algorithm finds small-sized connected dominating sets in a short time.
31393341
Compiling abstract scientific workflows into Web service workflows
The authors present an approach for compiling "scientist-friendly" abstract workflow specifications into real-world executable workflows of Web service invocations, using a set of abstract-as-view definitions from a repository of abstract tasks. There have been a number of proposals and systems for scientific workflow management. However, our approach features unique aspects, in particular: the separation of abstract and concrete executable workflows; and the use of database mediation techniques to automatically translate AWFs into EWFs.