6908840
Vigilante: end-to-end containment of internet worms
Worm containment must be automatic because worms can spread too fast for humans to respond. Recent work has proposed network-level techniques to automate worm containment; these techniques have limitations because there is no information about the vulnerabilities exploited by worms at the network level. We propose Vigilante, a new end-to-end approach to contain worms automatically that addresses these limitations. Vigilante relies on collaborative worm detection at end hosts, but does not require hosts to trust each other. Hosts run instrumented software to detect worms and broadcast self-certifying alerts (SCAs) upon worm detection. SCAs are proofs of vulnerability that can be inexpensively verified by any vulnerable host. When hosts receive an SCA, they generate filters that block infection by analysing the SCA-guided execution of the vulnerable software. We show that Vigilante can automatically contain fast-spreading worms that exploit unknown vulnerabilities without blocking innocuous traffic.
9292941
Chaff: engineering an efficient SAT solver
Boolean satisfiability is probably the most studied of the combinatorial optimization/search problems. Significant effort has been devoted to trying to provide practical solutions to this problem for problem instances encountered in a range of applications in electronic design automation (EDA), as well as in artificial intelligence (AI). This study has culminated in the development of several SAT packages, both proprietary and in the public domain (e.g. GRASP, SATO) which find significant use in both research and industry. Most existing complete solvers are variants of the Davis-Putnam (DP) search algorithm. In this paper we describe the development of a new complete solver, Chaff which achieves significant performance gains through careful engineering of all aspects of the search-especially a particularly efficient implementation of Boolean constraint propagation (BCP) and a novel low overhead decision strategy. Chaff has been able to obtain one to two orders of magnitude performance improvement on difficult SAT benchmarks in comparison with other solvers (DP or otherwise), including GRASP and SATO.
18035076
On Subsumption Removal and On-the-Fly CNF Simplification
CNF Boolean formulas generated from resolution or solution enumeration often have much redundancy. Efficient algorithms are needed to simplify and compact such CNF formulas. In this paper, we present a novel algorithm to maintain a subsumption-free CNF clause database by efficiently detecting and removing subsumption as the clauses are being added. We then present an algorithm that compact CNF formula further by applying resolutions to make it Decremental Resolution Free. Our experimental evaluations show that these algorithms are efficient and effective in practice.
11375306
A solver for quantified Boolean and linear constraints
We make a number of contributions to the understanding and practical resolution of quantified constraints. Unlike previous work in the CP literature that was essentially focused on constraints expressed as binary tables, we focus on Presburger Arithmetics, i.e., Boolean combinations of linear constraints. From a theoretical perspective, we clarify the problem of the treatment of universal quantifiers by proposing a "symmetric" version of the notion of quantified consistency. This notion imposes to maintain two constraint stores, which will be used to reason on universal and existential variables, respectively. We then describe a branch & bound algorithm that integrates both forms of propagation. Its implementation is, to the best of our knowledge, the first CP solver for this class of quantified constraints.
6734525
Propositional Satisfiability and Constraint Programming: A comparative survey
Propositional Satisfiability (SAT) and Constraint Programming (CP) have developed as two relatively independent threads of research cross-fertilizing 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 black-box approach, while CP aims at being tunable and programmable. This survey overviews the two areas in a comparative way, emphasizing the similarities and differences between the two and the points where we feel that one technology can benefit from ideas or experience acquired from the other.
14923930
Cache Performance of SAT Solvers: a Case Study for Efficient Implementation of Algorithms
We experimentally evaluate the cache performance of different SAT solvers as a case study for the efficient implementation of SAT algorithms. We evaluate several different Boolean Constraint Propagation (BCP) mechanisms and show their respective run time and cache performances on selected benchmark instances. From the experiments we conclude that a cache friendly data structure is a key element in the efficient implementation of SAT solvers. We also show empirical cache miss rates of several modern SAT solvers based on the Davis-Logemann-Loveland (DLL) algorithm with learning and non-chronological backtracking. We conclude that the recently developed SAT solvers are much more cache friendly in data structures and algorithm implementations compared with their predecessors.
11022941
XML-Based Advanced UDDI Search Mechanism for B2B Integration
Exploring appropriate business applications published as Web Services in UDDI registries is a critical issue. Search for such applications should be effective in terms of time and uniformed in terms of interfaces. In this paper, an XML-based advanced UDDI exploring engine, Business Explorer for Web Services (BE4WS), that provides developers with standard interfaces for efficiently searching business and service information in single or multiple UDDI registries is presented. The engine processes the proposed UDDI Search Markup Language (USML) that specifies a search request comprising multiple queries, UDDI sources, search criteria, and aggregation operator. The core component of BE4WS, Advanced UDDI Search Engine (AUSE), aggregates search results from different UDDI registries based on the USML request and built-in intelligent search facilities with the ability to cross-reference multiple categories. An aggregation example using BE4WS is demonstrated to enable easy B2B integration.
887255
An automated design tool for analog layouts
In this paper, a layout synthesis tool for the design of analog integrated circuits (ICs) is presented. This tool offers great flexibility that allows analog circuit designers to bring their special design knowledge and experiences into the synthesis process to create high-quality analog circuit layouts. Different from conventional layout systems that are limited to the optimization of single devices, our layout generation tool attempts to optimize more complex modules. This tool includes a complete tool suite that covers the following three major analog physical designs stages. 1) Module Generation: designers can develop and maintain their own technology- and application-independent module generators for subcircuits using an in-house developed description language. 2) Placement: a two-stage placement technique, tailored for the analog placement design, is proposed. In particular, this placement algorithm features a novel genetic placement stage followed by a fast simulated reannealing scheme. 3) Routing: the minimum-Steiner-tree-based global routing is developed, and it is actually integrated into the placement procedure to improve reliability and routability of the placement solutions. Following the global routing, a compaction-based constructive detailed routing finally completes the interconnection of the entire layout. Several testing circuits have been applied to demonstrate the design efficiency and the effectiveness of this tool. Experimental results show that this new layout tool is capable of producing high quality layouts comparable to those manually done by layout experts but with much less design time
14328389
Alternative scalable algorithms for lattice-based feature location
Considering the scalability of using formal concept analysis to locate features in source code, we present a set of alternative straightforward algorithms to achieve the same objectives. A preliminary experiment indicates that the alternative algorithms are more scalable to deal with the large numbers of data to some extent.
17777200
A similarity-aware approach to testing based fault localization
Debugging is a time-consuming task in software development and maintenance. To accelerate this task, several approaches have been proposed to automate fault localization. In particular, testing based fault localization (TBFL), which utilizes the testing information to localize the faults, seem to be very promising. However, the similarity between test cases in the test suite has been ignored in the research on TBFL. In this paper, we investigate this similarity issue and propose a novel approach named similarity-aware fault localization (SAFL), which can calculate the suspicion probability of each statement with little impact by the similarity issue. To address and deal with the similarity between test cases, SAFL applies the theory of fuzzy sets to remove the uneven distribution of the test cases. We also performed an experimental study for two real-world programs at different size levels to evaluate SAFL together with another two approaches to TBFL. Experimental results show that SAFL is more effective than the other two approaches when the test suites contain injected redundancy, and SAFL can achieve a competitive result with normal test suites. SAFL can also be more effective than applying test suite reduction to current approaches to TBFL.
1857778
Boosting image orientation detection with indoor vs. outdoor classification
Automatic detection of image orientation is a very important operation in photo image management. In this paper, we propose an automated method based on the boosting algorithm to estimate image orientations. The proposed method has the capability of rejecting images based on the confidence score of the orientation detection. Also, images are classified into indoor and outdoor, and this classification result is used to further refine the orientation detection. To select features more sensitive to the rotation, we combine the features by subtraction operation and select the most useful features by boosting algorithm. The proposed method has several advantages: small model size, fast classification speed, and effective rejection scheme.