77,490 research outputs found

    Rule-Based Software Verification and Correction

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    The increasing complexity of software systems has led to the development of sophisticated formal Methodologies for verifying and correcting data and programs. In general, establishing whether a program behaves correctly w.r.t. the original programmer s intention or checking the consistency and the correctness of a large set of data are not trivial tasks as witnessed by many case studies which occur in the literature. In this dissertation, we face two challenging problems of verification and correction. Specifically, verification and correction of declarative programs, and the verification and correction of Web sites (i.e. large collections of semistructured data). Firstly, we propose a general correction scheme for automatically correcting declarative, rule-based programs which exploits a combination of bottom-up as well as topdown inductive learning techniques. Our hybrid hodology is able to infer program corrections that are hard, or even impossible, to obtain with a simpler,automatic top-down or bottom-up learner. Moreover, the scheme will be also particularized to some well-known declarative programming paradigm: that is, the functional logic and the functional programming paradigm. Secondly, we formalize a framework for the automated verification of Web sites which can be used to specify integrity conditions for a given Web site, and then automatically check whether these conditions are fulfilled. We provide a rule-based, formal specification language which allows us to define syntactic as well as semantic properties of the Web site. Then, we formalize a verification technique which detects both incorrect/forbidden patterns as well as lack of information, that is, incomplete/missing Web pages. Useful information is gathered during the verification process which can be used to repair the Web site. So, after a verification phase, one can also infer semi-automatically some possible corrections in order to fix theWeb site. The methodology is based on a novel rewritBallis, D. (2005). Rule-Based Software Verification and Correction [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/194

    Where are your Manners? Sharing Best Community Practices in the Web 2.0

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    The Web 2.0 fosters the creation of communities by offering users a wide array of social software tools. While the success of these tools is based on their ability to support different interaction patterns among users by imposing as few limitations as possible, the communities they support are not free of rules (just think about the posting rules in a community forum or the editing rules in a thematic wiki). In this paper we propose a framework for the sharing of best community practices in the form of a (potentially rule-based) annotation layer that can be integrated with existing Web 2.0 community tools (with specific focus on wikis). This solution is characterized by minimal intrusiveness and plays nicely within the open spirit of the Web 2.0 by providing users with behavioral hints rather than by enforcing the strict adherence to a set of rules.Comment: ACM symposium on Applied Computing, Honolulu : \'Etats-Unis d'Am\'erique (2009

    Electronic Employment Eligibility Verification

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    [Excerpt] Unauthorized immigration and unauthorized employment continue to be key issues in the ongoing debate over immigration policy. Today’s discussions about these issues build on the work of prior Congresses. In 1986, following many years of debate about unauthorized immigration to the United States, Congress passed the Immigration Reform and Control Act (IRCA). This law sought to address unauthorized immigration, in part, by requiring all employers to examine documents presented by new hires to verify identity and work authorization and to complete and retain employment eligibility verification (I 9) forms. Ten years later, in the face of a growing unauthorized population, Congress attempted to strengthen the employment verification process by establishing pilot programs for electronic verification, as part of the Illegal Immigration Reform and Immigrant Responsibility Act of 1996 (IIRIRA). The Basic Pilot program (known today as E Verify), the first of the three IIRIRA employment verification pilots to be implemented and the only one still in operation, began in November 1997. Originally scheduled to terminate in November 2001, it has been extended several times. It is currently authorized until September 30, 2018, in accordance with the Consolidated Appropriations Act, 2018 (P.L. 115 141). E Verify is administered by the Department of Homeland Security’s (DHS’s) U.S. Citizenship and Immigration Services (USCIS). As of April 2, 2018, there were 779,722 employers enrolled in E Verify, representing more than 2.5 million hiring sites. E Verify is a largely voluntary program, but there are some mandatory participation requirements. Among them is a rule, which became effective in 2009, requiring certain federal contracts to contain a new clause committing contractors to use E Verify. Under E Verify, participating employers enter information about their new hires (name, date of birth, Social Security number, immigration/citizenship status, and alien number, if applicable) into an online system. This information is automatically compared with information in Social Security Administration and, if necessary, DHS databases to verify identity and employment eligibility. Legislation on electronic employment eligibility verification has been considered in recent Congresses. In weighing proposals on electronic employment verification, Congress may find it useful to evaluate them in terms of their potential impact on a set of related issues: unauthorized employment; verification system accuracy, efficiency, and capacity; discrimination; employer compliance; privacy; and verification system usability and employer burden

    The Anonymous Poster: How to Protect Internet Users’ Privacy and Prevent Abuse

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    The threat of anonymous Internet posting to individual privacy has been met with congressional and judicial indecisiveness. Part of the problem stems from the inherent conflict between punishing those who disrespect one\u27s privacy by placing a burden on the individual websites and continuing to support the Internet\u27s development. Additionally, assigning traditional tort liability is problematic as the defendant enjoys an expectation of privacy as well, creating difficulty in securing the necessary information to proceed with legal action. One solution to resolving invasion of privacy disputes involves a uniform identification verification program that ensures user confidentiality while promoting accountability for malicious behavior

    ADsafety: Type-Based Verification of JavaScript Sandboxing

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    Web sites routinely incorporate JavaScript programs from several sources into a single page. These sources must be protected from one another, which requires robust sandboxing. The many entry-points of sandboxes and the subtleties of JavaScript demand robust verification of the actual sandbox source. We use a novel type system for JavaScript to encode and verify sandboxing properties. The resulting verifier is lightweight and efficient, and operates on actual source. We demonstrate the effectiveness of our technique by applying it to ADsafe, which revealed several bugs and other weaknesses.Comment: in Proceedings of the USENIX Security Symposium (2011

    Computational identification of ubiquitylation sites from protein sequences

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    <p>Abstract</p> <p>Background</p> <p>Ubiquitylation plays an important role in regulating protein functions. Recently, experimental methods were developed toward effective identification of ubiquitylation sites. To efficiently explore more undiscovered ubiquitylation sites, this study aims to develop an accurate sequence-based prediction method to identify promising ubiquitylation sites.</p> <p>Results</p> <p>We established an ubiquitylation dataset consisting of 157 ubiquitylation sites and 3676 putative non-ubiquitylation sites extracted from 105 proteins in the UbiProt database. This study first evaluates promising sequence-based features and classifiers for the prediction of ubiquitylation sites by assessing three kinds of features (amino acid identity, evolutionary information, and physicochemical property) and three classifiers (support vector machine, <it>k</it>-nearest neighbor, and NaĂŻveBayes). Results show that the set of used 531 physicochemical properties and support vector machine (SVM) are the best kind of features and classifier respectively that their combination has a prediction accuracy of 72.19% using leave-one-out cross-validation.</p> <p>Consequently, an informative physicochemical property mining algorithm (IPMA) is proposed to select an informative subset of 531 physicochemical properties. A prediction system UbiPred was implemented by using an SVM with the feature set of 31 informative physicochemical properties selected by IPMA, which can improve the accuracy from 72.19% to 84.44%. To further analyze the informative physicochemical properties, a decision tree method C5.0 was used to acquire if-then rule-based knowledge of predicting ubiquitylation sites. UbiPred can screen promising ubiquitylation sites from putative non-ubiquitylation sites using prediction scores. By applying UbiPred, 23 promising ubiquitylation sites were identified from an independent dataset of 3424 putative non-ubiquitylation sites, which were also validated by using the obtained prediction rules.</p> <p>Conclusion</p> <p>We have proposed an algorithm IPMA for mining informative physicochemical properties from protein sequences to build an SVM-based prediction system UbiPred. UbiPred can predict ubiquitylation sites accompanied with a prediction score each to help biologists in identifying promising sites for experimental verification. UbiPred has been implemented as a web server and is available at <url>http://iclab.life.nctu.edu.tw/ubipred</url>.</p
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