5653745
Foundational Certified Code in a Metalogical Framework
Foundational certified code systems seek to prove untrusted programs to be safe relative to safety policies given in terms of actual machine architectures, thereby improving the systems’ flexibility and extensibility. Previous efforts have employed a structure wherein the proofs are expressed in the same logic used to express the safety policy. We propose an alternative structure wherein safety proofs are expressed in the Twelf metalogic, thereby eliminating from those proofs an extra layer of encoding needed in the previous accounts. Using this metalogical approach, we have constructed a complete, foundational account of safety for a fully expressive typed assembly language.
1395675
Small Proof Witnesses for LF
We instrument a higher-order logic programming search procedure to generate and check small proof witnesses for the Twelf system, an implementation of the logical framework LF. In particular, we extend and generalize ideas from Necula and Rahul [16] in two main ways: 1) We consider the full fragment of LF including dependent types and higher-order terms and 2) We study the use of caching of sub-proofs to further compact proof representations. Our experimental results demonstrate that many of the restrictions in previous work can be overcome and generating and checking small witnesses within Twelf provides valuable addition to its general safety infrastructure.
33218100
A Distance-Based Approach to Entity Reconciliation in Heterogeneous Databases
In modern organizations, decision makers must often be able to quickly access information from diverse sources in order to make timely decisions. A critical problem facing many such organizations is the inability to easily reconcile the information contained in heterogeneous data sources. To overcome this limitation, an organization must resolve several types of heterogeneity problems that may exist across different sources. We examine one such problem called the entity heterogeneity problem, which arises when the same real-world entity type is represented using different identifiers in different applications. A decision-theoretic model to resolve the problem is proposed. Our model uses a distance measure to express the similarity between two entity instances. We have implemented the model and tested it on real-world data. The results indicate that the model performs quite well in terms of its ability to predict whether two entity instances should be matched or not. The model is shown to be computationally efficient. It also scales well to large relations from the perspective of the accuracy of prediction. Overall, the test results imply that this is certainly a viable approach in practical situations.
3382815
PSQL: A Query Language for Probabilistic Relational Data
Abstract Database systems based on the relational model have become very popular for the storage of large volumes of business-related data. Although the relational model provides a great range of advantages over other data models, it was designed to support deterministic data and, consequently, it lacks a comprehensive way for handling uncertain data. However, in all real-world environments, uncertainty in data values is a common occurrence. Therefore, there is a need to extend the relational model so that data uncertainty can be captured explicitly. In an earlier work, we have proposed a probabilistic relational algebra that is a consistent extension of the conventional relational algebra and is reducible to the latter. The contribution of this work is the development of a non-procedural probabilistic query language—structured around the popular SQL—that can be built on top of that algebra. We formalize the extended syntax, provide examples to illustrate the syntax, and examine query formulation from a decision-theoretic perspective.
19572588
Web Site Personalization Using User Profile Information
In this paper we discuss a technique for web site personalization. Connectivity analysis has been shown to be useful in identifying high quality web pages within a topic or domain specific graph of hyper linked documents. We have implemented a system that creates a view of a subset of a web site most relevant to a given user. This sort of personalization is useful for filtering a useful subset of a site so that the user gets a low volume of quality information. The essence of our approach is to augment a previous connectivity analysis with content analysis. We present an agent which assists the user when he browses and distills a personalized sub graph of the website based on his user profile.
4723885
Learning while solving problems in best first search
We investigate the role of learning in search-based systems for solving optimization problems. We use a learning model, where the values of a set of features can be used to induce a clustering of the problem state space. The feasible set of h* values corresponding to each cluster is called h*set. If we relax the optimality guarantee, and tolerate a risk factor, the distribution of h*set can be used to expedite search and produce results within a given risk of suboptimality. The off-line learning method consists of solving a batch of problems by using A* to learn the distribution of the h*set in the learning phase. This distribution can be used to solve the rest of the problems effectively. We show how the knowledge acquisition phase can be integrated with the problem solving phase. We present a continuous online learning scheme that uses an "anytime" algorithm to learn continuously while solving problems.
27571789
Computation of intraprocedural dynamic program slices
Abstract Dynamic slicing algorithms are used in interactive applications such as program debugging and testing. Therefore, these algorithms need to be very efficient. In this context, we propose three intraprocedural dynamic slicing algorithms which are more space and time efficient than the existing algorithms. Two of the proposed algorithms compute precise dynamic slices of structured programs using Program Dependence Graph as an intermediate representation. To compute precise dynamic slices of unstructured programs, we introduce the concepts of jump dependence and Unstructured Program Dependence Graph. The third algorithm uses Unstructured Program Dependence Graph as the intermediate program representation, and computes precise dynamic slices of unstructured programs. We show that each of our proposed algorithms is more space and time efficient than the existing algorithms.