eprintid: 1490740
rev_number: 27
eprint_status: archive
userid: 608
dir: disk0/01/49/07/40
datestamp: 2016-05-07 22:30:32
lastmod: 2021-10-10 22:52:25
status_changed: 2017-05-30 13:03:37
type: proceedings_section
metadata_visibility: show
creators_name: Jia, Y
creators_name: Cohen, MB
creators_name: Harman, M
creators_name: Petke, J
title: Learning Combinatorial Interaction Test Generation Strategies Using Hyperheuristic Search
ispublished: pub
divisions: UCL
divisions: B04
divisions: C05
divisions: F48
keywords: Science & technology, technology, computer science, software engineering, engineering, electrical & electronic, computer science, engineering, interaction test suites, heuristics, system, State.
note: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
abstract: The surge of search based software engineering research has been hampered by the need to develop customized search algorithms for different classes of the same problem. For instance, two decades of bespoke Combinatorial Interaction Testing (CIT) algorithm development, our exemplar problem, has left software engineers with a bewildering choice of CIT techniques, each specialized for a particular task. This paper proposes the use of a single hyperheuristic algorithm that learns search strategies across a broad range of problem instances, providing a single generalist approach. We have developed a Hyperheuristic algorithm for CIT, and report experiments that show that our algorithm competes with known best solutions across constrained and unconstrained problems: For all 26 real-world subjects, it equals or outperforms the best result previously reported in the literature. We also present evidence that our algorithm's strong generic performance results from its unsupervised learning. Hyperheuristic search is thus a promising way to relocate CIT design intelligence from human to machine.
date: 2015-05-24
date_type: published
publisher: IEEE
official_url: http://dx.doi.org/10.1109/ICSE.2015.71
oa_status: green
full_text_type: other
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1088290
doi: 10.1109/ICSE.2015.71
isbn_13: 9781479919345
lyricists_name: Harman, Mark
lyricists_name: Jia, Yue
lyricists_name: Petke, Justyna
lyricists_id: MHARM36
lyricists_id: YJIAX90
lyricists_id: JPETK66
actors_name: Jia, Yue
actors_name: Cuccu, Clara
actors_id: YJIAX90
actors_id: CCCUC40
actors_role: owner
actors_role: impersonator
full_text_status: public
series: Software Engineering (ICSE)
publication: 2015 IEEE/ACM 37TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, VOL 1
volume: 37
place_of_pub: Florence, Italy
pagerange: 540-550
pages: 11
event_title: 2015 IEEE ACM 37th IEEE International Conference on Software Engineering
event_location: Florence, ITALY
event_dates: 16 May 2015 - 24 May 2015
institution: 2015 IEEE ACM 37th IEEE International Conference on Software Engineering
book_title: Proceedings of 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering
editors_name: Bertolino, A
editors_name: Elbaum, S
editors_name: Canfora, G
citation:        Jia, Y;    Cohen, MB;    Harman, M;    Petke, J;      (2015)    Learning Combinatorial Interaction Test Generation Strategies Using Hyperheuristic Search.                     In: Bertolino, A and Elbaum, S and Canfora, G, (eds.) Proceedings of 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.  (pp. pp. 540-550).  IEEE: Florence, Italy.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/1490740/1/Jia_Learning_Combinatorial_2015_ICSE.pdf