Debugging ASP using ILP

Tingting Li, Marina De Vos, Julian Padget, Ken Satoh, Tina Balke

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Declarative programming allows the expression of properties of the desired solution(s), while the computational task is delegated to a general-purpose algorithm. The freedom from explicit control
is counter-balanced by the difficulty in working out what properties are missing or are incorrectly expressed, when the solutions do not meet expectations. This can be particularly problematic in the
case of answer set semantics, because the absence of a key constraint/rule could make the difference between none or thousands of answer sets, rather than the intended one (or handful). The debugging
task then comprises adding or deleting conditions on the right hand sides of existing rules or, more far-reaching, adding or deleting whole rules. The contribution of this paper is to show how inductive
logic programming (ILP) along with examples of (un)desirable properties of answer sets can be used to revise the original program semi-automatically so that it satisfies the stated properties, in effect
providing debugging-by-example for programs under answer set semantics.
LanguageEnglish
Title of host publicationProceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015)
EditorsMarina De Vos, Thomas Eiter, Yuliya Lierler, Francesca Toni
PublisherCEUR
Pages1 - 14
Number of pages14
VolumeVol-1433
ISBN (Electronic)1613-0073
StatusPublished - Aug 2015

Fingerprint

Inductive logic programming (ILP)
Semantics
Computer programming

Cite this

Li, T., De Vos, M., Padget, J., Satoh, K., & Balke, T. (2015). Debugging ASP using ILP. In M. De Vos, T. Eiter, Y. Lierler, & F. Toni (Eds.), Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015) (Vol. Vol-1433, pp. 1 - 14). CEUR.

Debugging ASP using ILP. / Li, Tingting; De Vos, Marina; Padget, Julian; Satoh, Ken; Balke, Tina.

Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015) . ed. / Marina De Vos; Thomas Eiter; Yuliya Lierler; Francesca Toni. Vol. Vol-1433 CEUR, 2015. p. 1 - 14.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Li, T, De Vos, M, Padget, J, Satoh, K & Balke, T 2015, Debugging ASP using ILP. in M De Vos, T Eiter, Y Lierler & F Toni (eds), Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015) . vol. Vol-1433, CEUR, pp. 1 - 14.
Li T, De Vos M, Padget J, Satoh K, Balke T. Debugging ASP using ILP. In De Vos M, Eiter T, Lierler Y, Toni F, editors, Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015) . Vol. Vol-1433. CEUR. 2015. p. 1 - 14.
Li, Tingting ; De Vos, Marina ; Padget, Julian ; Satoh, Ken ; Balke, Tina. / Debugging ASP using ILP. Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015) . editor / Marina De Vos ; Thomas Eiter ; Yuliya Lierler ; Francesca Toni. Vol. Vol-1433 CEUR, 2015. pp. 1 - 14
@inproceedings{ec7ae5bfc0ef47ae80f30ef9a5024d8a,
title = "Debugging ASP using ILP",
abstract = "Declarative programming allows the expression of properties of the desired solution(s), while the computational task is delegated to a general-purpose algorithm. The freedom from explicit controlis counter-balanced by the difficulty in working out what properties are missing or are incorrectly expressed, when the solutions do not meet expectations. This can be particularly problematic in thecase of answer set semantics, because the absence of a key constraint/rule could make the difference between none or thousands of answer sets, rather than the intended one (or handful). The debuggingtask then comprises adding or deleting conditions on the right hand sides of existing rules or, more far-reaching, adding or deleting whole rules. The contribution of this paper is to show how inductivelogic programming (ILP) along with examples of (un)desirable properties of answer sets can be used to revise the original program semi-automatically so that it satisfies the stated properties, in effectproviding debugging-by-example for programs under answer set semantics.",
author = "Tingting Li and {De Vos}, Marina and Julian Padget and Ken Satoh and Tina Balke",
year = "2015",
month = "8",
language = "English",
volume = "Vol-1433",
pages = "1 -- 14",
editor = "{De Vos}, Marina and Thomas Eiter and Yuliya Lierler and Francesca Toni",
booktitle = "Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015)",
publisher = "CEUR",

}

TY - GEN

T1 - Debugging ASP using ILP

AU - Li,Tingting

AU - De Vos,Marina

AU - Padget,Julian

AU - Satoh,Ken

AU - Balke,Tina

PY - 2015/8

Y1 - 2015/8

N2 - Declarative programming allows the expression of properties of the desired solution(s), while the computational task is delegated to a general-purpose algorithm. The freedom from explicit controlis counter-balanced by the difficulty in working out what properties are missing or are incorrectly expressed, when the solutions do not meet expectations. This can be particularly problematic in thecase of answer set semantics, because the absence of a key constraint/rule could make the difference between none or thousands of answer sets, rather than the intended one (or handful). The debuggingtask then comprises adding or deleting conditions on the right hand sides of existing rules or, more far-reaching, adding or deleting whole rules. The contribution of this paper is to show how inductivelogic programming (ILP) along with examples of (un)desirable properties of answer sets can be used to revise the original program semi-automatically so that it satisfies the stated properties, in effectproviding debugging-by-example for programs under answer set semantics.

AB - Declarative programming allows the expression of properties of the desired solution(s), while the computational task is delegated to a general-purpose algorithm. The freedom from explicit controlis counter-balanced by the difficulty in working out what properties are missing or are incorrectly expressed, when the solutions do not meet expectations. This can be particularly problematic in thecase of answer set semantics, because the absence of a key constraint/rule could make the difference between none or thousands of answer sets, rather than the intended one (or handful). The debuggingtask then comprises adding or deleting conditions on the right hand sides of existing rules or, more far-reaching, adding or deleting whole rules. The contribution of this paper is to show how inductivelogic programming (ILP) along with examples of (un)desirable properties of answer sets can be used to revise the original program semi-automatically so that it satisfies the stated properties, in effectproviding debugging-by-example for programs under answer set semantics.

UR - http://ceur-ws.org/Vol-1433/tc_26.pdf

UR - http://ceur-ws.org/Vol-1433/

M3 - Conference contribution

VL - Vol-1433

SP - 1

EP - 14

BT - Proceedings of the Technical Communications of the 31st International Conference on Logic Programming (ICLP 2015)

PB - CEUR

ER -