Abstract We introduce astepping methodologyfor answer-set programming (ASP) that allows for debugging answer-set programs and is based on the stepwise application of rules. Similar to debugging in imperative languages, where the behaviour of a program is observed during a step-by-step execution, stepping for ASP allows for observing the effects that rule applications have in the computation of an answer set. While the approach is inspired from debugging in imperative programming, it is conceptually different to stepping in other paradigms due to non-determinism and declarativity that are inherent to ASP. In particular, unlike statements in an imperative program that are executed following a strict control flow, there is no predetermined order in which to consider rules in ASP during a computation. In our approach, the user is free to decide which rule to consider active in the next step following his or her intuition. This way, one can focus on interesting parts of the debugging search space. Bugs are detected during stepping by revealing differences between the actual semantics of the program and the expectations of the user. As a solid formal basis for stepping, we develop a framework of computations for answer-set programs. For fully supporting different solver languages, we build our framework on an abstract ASP language that is sufficiently general to capture different solver languages. To this end, we make use of abstract constraints as an established abstraction for popular language constructs such as aggregates. Stepping has been implemented inSeaLion, an integrated development environment for ASP. We illustrate stepping using an example scenario and discuss the stepping plugin ofSeaLion. Moreover, we elaborate on methodological aspects and the embedding of stepping in the ASP development process.

We introduce a general framework for analyzing realizability in abstract dialectical frameworks (ADFs) and various of its subclasses. In particular, the framework applies to Dung argumentation frameworks, SETAFs by Nielsen and Parsons, and bipolar ADFs. We present a uniform characterization method for the admissible, complete, preferred and model/stable semantics. We employ this method to devise an algorithm that decides realizability for the mentioned formalisms and semantics; moreover the algorithm allows for constructing a desired knowledge base whenever one exists. The algorithm is built in a modular way and thus easily extensible to new formalisms and semantics. We have implemented our approach in answer set programming, and used the implementation to obtain several novel results on the relative expressiveness of the abovemen-tioned formalisms.

We show in this paper how managed multi-context systems (mMCS) can be turned into a reactive formalism suitable for continuous reasoning in dynamic environments. We extend mMCS with (abstract) sensors and define the notion of a run of the extended systems. We then show how typical problems arising in online reasoning can be addressed: handling potentially inconsistent sensor input, modeling intelligent forms of forgetting, and controlling the reasoning effort spent by contexts. We also investigate the complexity of some important related decision problems.

Abstract In this paper, we present SeaLion, an integrated development environment (IDE) for answer-set programming (ASP). SeaLion provides source-code editors for the languages of Gringo and DLV and offers popular amenities like syntax highlighting, syntax checking, code completion, visual program outline, and refactoring functionality. The tool has been realised in the context of a research project whose goal is the development of techniques to support the practical coding process of answer-set programs. In this respect, SeaLion is the first IDE for ASP that provides debugging features that work for real-world answer-set programs and supports the rich languages of modern answer-set solvers. Indeed, SeaLion implements a stepping-based debugging approach that allows the developer to quickly track down programming errors by simply following his or her intuitions on the intended semantics. Besides that, SeaLion supports ASP development using model-driven engineering techniques including domain modelling with extended UML class diagrams and visualisation of answer sets in corresponding instance diagrams. Moreover, customised visualisation as well as visual editing of answer sets is realised by the Kara plugin of SeaLion. Further implemented features are a documentation generator based on the Lana annotation language, support for external solvers, and interoperability with external tools. SeaLion comes as a plugin of the popular Eclipse platform and provides interfaces for future extensions of the IDE.

Abstract 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.

Answer-set programming (ASP) is a well-acknowledged paradigm for declarative problem solving, yet comparably little effort has been spent on the investigation of methods to support the development of answer-set programs. In particular, systematic testing of programs, constituting an integral part of conventional software development, has not been discussed for ASP thus far. In this paper, we fill this gap and develop notions enabling the structural testing of answer-set programs, i.e., we address testing based on test cases that are chosen with respect to the internal structure of a given answer-set program. More specifically, we introduce different notions of coverage that measure to what extent a collection of test inputs covers certain important structural components of the program. In particular, we introduce metrics corresponding to path and branch coverage from conventional testing. We also discuss complexity aspects of the considered notions and give strategies how test inputs that yield increasing (up to total) coverage can be automatically generated.

In W3C's Rule Interchange Format (RIF), F-Logic rules have received considerable attention as a major logical rule formalism, while combinations of rules with Description Logic (DL) ontologies in RIF, let alone with F-Logic rules, are far less developed. To mend this, we first present F-Logic# knowledge bases, a framework based on the semantics of the well-investigated dl-programs, that provides a loose coupling approach to integrating F-Logic rules and DL ontologies by allowing rules to query the ontology using external atoms. We investigate the semantical properties of this framework and define a stratified fragment that allows for fast reasoning - a necessity on a Web with large amounts of data. We then shape F-Logic# as a RIF dialect, setting it firmly in a Web context and providing an expressive combination of F-Logic rules with DL ontologies in RIF. Finally, we show how to extend the F-Logic rule engine OntoBroker towards reasoning with F-Logic#, enabling as such a first commercial implementation for loosely-coupled ontologies and rules.

Abstract 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.

Abstract 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 fordebuggingan 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 answer set. 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.