Interactive Debugging of Non-ground ASP Programs

Dodaro, Carmine; Gasteiger, Philip; Musitsch, Benjamin; Ricca, Francesco; Shchekotykhin, Kostyantyn

doi:10.1007/978-3-319-23264-5_24

Cited by 12 publications

(15 citation statements)

References 15 publications

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“…Syrjänen's diagnosis technique (Syrjänen 2006) is limited to the setting when a program has no answer set at all. The same holds for the work of Dodaro et al (2015), however the authors demonstrate how other debugging problems can be reduced to that of inconsistency. The method requires an intended answer set but offers the means to generate that in an interactive way, building on the technique by Shchekotykhin (2015).…”

Section: Related Workmentioning

confidence: 58%

“…In a related approach, Dodaro et al (2015) use control atoms quite similar to that of the tagging approach (Brain et al 2007b;Pührer 2007) to identify sets of rules that lead to inconsistency of a program under the requirement that a given set of atoms is true in some intended answer set. An implementation is provided that profits from a tight integration with the ASP solver WASP (Alviano et al 2015).…”

Section: Related Workmentioning

confidence: 99%

“…Besides stepping, also the approaches by Wittocx et al (2009) and Dodaro et al (2015) as well as Shchekotykhin (2015) can be considered interactive. While in the approach of Wittocx et al a fixed proof is explored interactively, the interaction in our method has influence on the direction of the computation.…”

Section: Related Workmentioning

confidence: 99%

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Stepwise debugging of answer-set programs

Oetsch¹,

Pührer²,

Tompits³

2017

Theory and Practice of Logic Programming

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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.

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Section: Related Workmentioning

confidence: 58%

Section: Related Workmentioning

confidence: 99%

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Stepwise debugging of answer-set programs

Oetsch¹,

Pührer²,

Tompits³

2017

Theory and Practice of Logic Programming

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“…Examples of such environments are the MiniZinc IDE for constraint modeling [57], Protégé, which supports the creation of ontologies [58], ASPIDE as a tool for the development of Answer Set Programs [59], as well as various Prolog IDEs like SWI-Prolog [60]. Several of these IDEs come with embedded debugging support or can be extended with external tools like the OntoDebug plug-in used in this paper [61,62,25].…”

Section: Usefulness Analysis Of Toolsmentioning

confidence: 99%

“…Ontology debugging was also the task in the user studies reported in this paper, where the participants used the OntoDebug 2 debugging plug-in [25] of the popular ontology editing tool Protégé [27]. 3 The underlying principles and algorithms of the debugging approach are, however, not limited to ontologies and can be applied for various forms of knowledge representation and reasoning, see [20,67,61,68].…”

Section: Background: Knowledge Base Debugging With Mbdmentioning

confidence: 99%

Are query-based ontology debuggers really helping knowledge engineers?

Rodler

Jannach

Schekotihin

et al. 2019

Knowledge-Based Systems

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Real-world semantic or knowledge-based systems, e.g., in the biomedical domain, can become large and complex. Tool support for the localization and repair of faults within knowledge bases of such systems can therefore be essential for their practical success. Correspondingly, a number of knowledge base debugging approaches, in particular for ontology-based systems, were proposed throughout recent years. Query-based debugging is a comparably recent interactive approach that localizes the true cause of an observed problem by asking knowledge engineers a series of questions. Concrete implementations of this approach exist, such as the OntoDebug plug-in for the ontology editor Protégé.To validate that a newly proposed method is favorable over an existing one, researchers often rely on simulation-based comparisons. Such an evaluation approach however has certain limitations and often cannot fully inform us about a method's true usefulness. We therefore conducted different user studies to assess the practical value of query-based ontology debugging. One main insight from the studies is that the considered interactive approach is indeed more efficient than an alternative algorithmic debugging based on test cases. We also observed that users frequently made errors in the process, which highlights the importance of a careful design of the queries that users need to answer.

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$$\mathsf {Uhura}$$ : An Authoring Tool for Specifying Answer-Set Programs Using Controlled Natural Language

Kain

Tompits

2019

Logics in Artificial Intelligence

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Interactive Debugging of Non-ground ASP Programs

Cited by 12 publications

References 15 publications

Stepwise debugging of answer-set programs

Stepwise debugging of answer-set programs

Are query-based ontology debuggers really helping knowledge engineers?

$$\mathsf {Uhura}$$ : An Authoring Tool for Specifying Answer-Set Programs Using Controlled Natural Language

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