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Performance Tuning in Answer Set Programming

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9345))

Abstract

Performance analysis and tuning are well established software engineering processes in the realm of imperative programming. This work is a step towards establishing the standards of performance analysis in the realm of answer set programming – a prominent constraint programming paradigm. We present and study the roles of human tuning and automatic configuration tools in this process. The case study takes place in the realm of a real-world answer set programming application that required several hundred lines of code. Experimental results suggest that human-tuning of the logic programming encoding and automatic tuning of the answer set solver are orthogonal (complementary) issues.

We would like to thank Joshua Irvin, Marius Lindauer, Peter Schüller, Benjamin Susman, Miroslaw Truszczynski, and Victor Winter for valuable discussions related to this paper as well as anonymous reviewers for their comments.

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Notes

  1. 1.

    http://potassco.sourceforge.net/.

  2. 2.

    Terms Concretion and Projection were coined by Gebser et al. [5].

  3. 3.

    http://www.cis.upenn.edu/~treebank/.

  4. 4.

    http://www.cs.ubc.ca/labs/beta/Projects/SMAC/.

  5. 5.

    http://www.cs.uni-potsdam.de/piclasp/.

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Correspondence to Matthew Buddenhagen .

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Buddenhagen, M., Lierler, Y. (2015). Performance Tuning in Answer Set Programming. In: Calimeri, F., Ianni, G., Truszczynski, M. (eds) Logic Programming and Nonmonotonic Reasoning. LPNMR 2015. Lecture Notes in Computer Science(), vol 9345. Springer, Cham. https://doi.org/10.1007/978-3-319-23264-5_17

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  • DOI: https://doi.org/10.1007/978-3-319-23264-5_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23263-8

  • Online ISBN: 978-3-319-23264-5

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