Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we pr...
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Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we present the tool Kato for supporting the detection of this kind of plagiarism in the area of answer-set programming (ASP). Currently, the tool is implemented for DLV programs but it is designed to handle other logic-programming dialects as well. We review the basic features of Kato, introduce its theoretical underpinnings, and discuss an application of Kato for plagiarism detection in the context of courses on logic programming at the Vienna University of Technology.
An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set progr...
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An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set program are recognised as a crucial step in this regard. Initial work on debugging in ASP mainly focused on propositional programs, yet practical debuggers need to handle programs with variables as well. In this paper, we discuss a debugging technique that is directly geared towards non-ground programs. Following previous work, we address the central debugging question why some interpretation is not an answerset. The explanations provided by our method are computed by means of a meta-programming technique, using a uniform encoding of a debugging request in terms of ASP itself. Our method also permits programs containing comparison predicates and integer arithmetics, thus covering a relevant language class commonly supported by all state-of-the-art ASP solvers.
While past research in answer-set programming (ASP) mainly focused on theory, ASP solver technology, and applications, the present work situates itself in the context of a quite recent research trend: development supp...
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While past research in answer-set programming (ASP) mainly focused on theory, ASP solver technology, and applications, the present work situates itself in the context of a quite recent research trend: development support for ASP. In particular, we propose to augment answer-set programs with additional meta-information formulated in a dedicated annotation language, called LANA. This language allows the grouping of rules into coherent blocks and to specify language signatures, types, pre- and postconditions, as well as unit tests for such blocks. While these annotations are invisible to an ASP solver, as they take the form of program comments, they can be interpreted by tools for documentation, testing, and verification purposes, as well as to eliminate sources of common programming errors by realising syntax checking or code completion features. To demonstrate its versatility, we introduce two such tools, viz. (i) ASPDOC, for generating an HTML documentation for a program based on the annotated information, and (ii) ASPUNIT, for running and monitoring unit tests on program blocks. LANA is also exploited in the SeaLion system, an integrated development environment for ASP based on Eclipse.
Many problems from the area of AI have been shown tractable for bounded treewidth. In order to put such results into practice, quite involved dynamic programming (DP) algorithms on tree decompositions have to be desig...
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Many problems from the area of AI have been shown tractable for bounded treewidth. In order to put such results into practice, quite involved dynamic programming (DP) algorithms on tree decompositions have to be designed and implemented. These algorithms typically show recurring patterns that call for tasks like subset minimization. In this paper we present a novel approach to obtain such DP algorithms from simpler principles, where the DP formalization of subset minimization is performed automatically. We first give a theoretical account of our novel method, and then present D-FLAT<^>2, a system that allows one to specify the core DP algorithm via answersetprogramming (ASP). We illustrate the approach at work by providing several DP algorithms that are more space-efficient than existing solutions, while featuring improved readability, reuse and therefore maintainability of ASP code. Experiments show that our approach also yields a significant improvement in runtime performance.
answer-set programming (ASP) is a powerful and expressive knowledge representation paradigm with a significant number of applications in logic-based AI. The traditional ground-and-solve approach, however, requires ASP...
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answer-set programming (ASP) is a powerful and expressive knowledge representation paradigm with a significant number of applications in logic-based AI. The traditional ground-and-solve approach, however, requires ASP programs to be grounded upfront and thus suffers from the so-called grounding bottleneck (i.e., ASP programs easily exhaust all available memory and thus become unsolvable). As a remedy, lazy-grounding ASP solvers have been developed, but many state-of-the-art techniques for grounded ASP solving have not been available to them yet. In this work we present, for the first time, adaptions to the lazy-grounding setting for many important techniques, like restarts, phase saving, domain-independent heuristics, and learned-clause deletion. Furthermore, we investigate their effects and in general observe a large improvement in solving capabilities and also uncover negative effects in certain cases, indicating the need for portfolio solving as known from other solvers.
Product configuration is a major industrial application domain for constraint satisfaction techniques. Conditional constraint satisfaction problems (CCSPs) and feature models (FMs) have been developed to represent con...
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Product configuration is a major industrial application domain for constraint satisfaction techniques. Conditional constraint satisfaction problems (CCSPs) and feature models (FMs) have been developed to represent configuration problems in a natural way. CCSPs are like constraint satisfaction problems (CSPs), but they also include potential variables, which might or might not exist in any given solution, as well as classical variables, which are required to take a value in every solution. CCSPs model, for example, options on a car, for which the style of sunroof (a variable) only makes sense if the car has a sunroof at all. FMs are directed acyclic graphs of features with constraints on edges. FMs model, for example, cell phone features, where utility functions are required, but the particular utility function "games" is optional, but requires Java support. We show that existing techniques from formal methods and answersetprogramming can be used to naturally model CCSPs and FMs. We demonstrate configurators in both approaches. An advantage of these approaches is that the model builder does not have to reformulate the CCSP or FM into a classic CSP, converting potential variables into classical variables by adding a "does not exist" value and modifying the problem constraints. Our configurators automatically reason about the model itself, enumerating all solutions and discovering several kinds of model flaws.
Extension-based argumentation semantics have shown to be a suitable approach for performing practical reasoning. An important concern in extension-based-argumentation semantics is the computational complexity of the d...
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ISBN:
(纸本)9781607506430;9781607506423
Extension-based argumentation semantics have shown to be a suitable approach for performing practical reasoning. An important concern in extension-based-argumentation semantics is the computational complexity of the decision problems that has been shown to range from NP-complete to Pi((p))(2)-complete. In this paper, we introduce a generic extension-based argumentation semantics solver, that is called WizArg. The WizArg project consists in two main components: The WizArg Argumentation library (that can be used by any generic software to solve argumentation frameworks and answer questions about extension-based-argumentation semantics) and the WizArg front-end (a generic software component that allows users to create, save, and load their own argumentation frameworks).
answer-set programming (ASP) is an established paradigm for declarative problem solving, yet comparably little work on testing of answer-set programs has been done so far. In a recent paper, foundations for structure-...
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ISBN:
(纸本)9783642208942;9783642208959
answer-set programming (ASP) is an established paradigm for declarative problem solving, yet comparably little work on testing of answer-set programs has been done so far. In a recent paper, foundations for structure-based testing of answer-set programs building on a number of coverage notions have been proposed. In this paper, we develop a framework for testing answer-set programs based on this work and study how good the structure-based approach to test input generation is compared to random test input generation. The results indicate that random testing is quite ineffective for some benchmarks, while structure-based techniques catch faults with a high rate more consistently also in these cases.
We pinpoint the limitations of existing approaches to the treatment of strong and default negation in answer-set program updates and formulate the early recovery principle that plausibly constrains their interaction.
ISBN:
(纸本)9783642405648
We pinpoint the limitations of existing approaches to the treatment of strong and default negation in answer-set program updates and formulate the early recovery principle that plausibly constrains their interaction.
An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set progr...
详细信息
An important issue towards a broader acceptance of answer-set programming (ASP) is the deployment of tools which support the programmer during the coding phase. In particular, methods for debugging an answer-set program are recognised as a crucial step in this regard. Initial work on debugging in ASP mainly focused on propositional programs, yet practical debuggers need to handle programs with variables as well. In this paper, we discuss a debugging technique that is directly geared towards non-ground programs. Following previous work, we address the central debugging question why some interpretation is not an answerset. The explanations provided by our method are computed by means of a meta-programming technique, using a uniform encoding of a debugging request in terms of ASP itself. Our method also permits programs containing comparison predicates and integer arithmetics, thus covering a relevant language class commonly supported by all state-of-the-art ASP solvers.
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