DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections

Oliver A. Tazl; Christopher Tafeit; Franz Wotawa; Alexander Felfernig

doi:10.18293/SEKE2022-172

DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections

Oliver A. Tazl, Christopher Tafeit, Franz Wotawa, Alexander Felfernig

Institute of Software Engineering and Artificial Intelligence (7160)

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Abstract

About two decades ago, two algorithms, i.e., DDMin and QuickXPlain, for minimizing collections, were independently proposed and gained attention in the two research areas of Software Engineering and Artificial Intelligence, respectively. Whereas DDMin was developed for reducing a given test case, QuickXPlain was intended to be used for obtaining minimal conflicts efficiently. In this paper, we compare the performance of both algorithms with respect to their capabilities of minimizing collections. We found out that one algorithm outperforms the other under given prerequisites and vice versa. These findings help to select the suitable algorithm for a given task.

Original language	English
Title of host publication	SEKE 2022 - Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering
Publisher	Knowledge Systems Institute Graduate School
Pages	481-486
Number of pages	6
ISBN (Electronic)	1891706543, 9781891706547
DOIs	https://doi.org/10.18293/SEKE2022-172
Publication status	Published - 2022
Event	34th International Conference on Software Engineering and Knowledge Engineering: SEKE 2022 - Pittsburgh, United States Duration: 1 Jul 2022 → 10 Jul 2022

Conference

Conference	34th International Conference on Software Engineering and Knowledge Engineering
Abbreviated title	SEKE 2022
Country/Territory	United States
City	Pittsburgh
Period	1/07/22 → 10/07/22

Keywords

application to diagnosis
configuration
conflict minimization
software testing
test case minimization

ASJC Scopus subject areas

Software

Access to Document

10.18293/SEKE2022-172

Cite this

Tazl, O. A., Tafeit, C., Wotawa, F., & Felfernig, A. (2022). DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections. In SEKE 2022 - Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering (pp. 481-486). Knowledge Systems Institute Graduate School. https://doi.org/10.18293/SEKE2022-172

DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections. / Tazl, Oliver A.; Tafeit, Christopher; Wotawa, Franz et al.
SEKE 2022 - Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering. Knowledge Systems Institute Graduate School, 2022. p. 481-486.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Tazl, OA, Tafeit, C, Wotawa, F & Felfernig, A 2022, DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections. in SEKE 2022 - Proceedings of the 34th International Conference on Software Engineering and Knowledge Engineering. Knowledge Systems Institute Graduate School, pp. 481-486, 34th International Conference on Software Engineering and Knowledge Engineering, Pittsburgh, United States, 1/07/22. https://doi.org/10.18293/SEKE2022-172

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DDMin versus QuickXplain - An Experimental Comparison of two Algorithms for Minimizing Collections

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Keywords

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