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Explanations for over-constrained problems using QuickXPlain with speculative executions

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Abstract

Conflict detection is used in various scenarios ranging from interactive decision making (e.g., knowledge-based configuration) to the diagnosis of potentially faulty models (e.g., using knowledge base analysis operations). Conflicts can be regarded as sets of restrictions (constraints) causing an inconsistency. Junker’s QuickXPlain is a divide-and-conquer based algorithm for the detection of preferred minimal conflicts. In this article, we present a novel approach to the detection of such conflicts which is based on speculative programming. We introduce a parallelization of QuickXPlain and empirically evaluate this approach on the basis of synthesized knowledge bases representing feature models. The results of this evaluation show significant performance improvements in the parallelized QuickXPlain version.

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Notes

  1. Note that this representation can be easily translated into a specific solver representation – see, for example, choco-solver.org.

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Acknowledgements

This work has been partially funded by the EU FEDER program, the ParXCel project (880657) funded by the Austrian Research Promotion Agency, the MINECO project OPHELIA (RTI2018-101204-B-C22), the TASOVA network (MCIU-AEI TIN2017-90644-REDT), and the Junta de Andalucia METAMORFOSIS project. We want to thank Jesús Giráldez from the University of Granada as well as Rafael Corchuelo and Mayte Gómez–López from the University of Sevilla for providing feedback in early stages of this research.

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Authors and Affiliations

  1. Departamento de Administración, Universidad Católica del Norte, Antofagasta, Chile

    Cristian Vidal

  2. Institute of Software Technology, Graz University of Technology, Graz, Austria

    Alexander Felfernig & Müslüm Atas

  3. Computer Languages & Systems, ETSI Informática, University of Seville, Sevilla, Spain

    José Galindo & David Benavides

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  1. Cristian Vidal
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  2. Alexander Felfernig
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  4. Müslüm Atas
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  5. David Benavides
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Correspondence to Cristian Vidal.

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The software, material and results used during the runtime analysis can be accessed through https://doi.org/10.5281/zenodo.3825090

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Vidal, C., Felfernig, A., Galindo, J. et al. Explanations for over-constrained problems using QuickXPlain with speculative executions. J Intell Inf Syst 57, 491–508 (2021). https://doi.org/10.1007/s10844-021-00675-4

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