Adaptive selection of helper-objectives for test case generation

Maxim Buzdalov; Arina Buzdalova

doi:10.1109/CEC.2013.6557836

Adaptive selection of helper-objectives for test case generation

Maxim Buzdalov, Arina Buzdalova

ITMO University

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

15 Dyfyniadau (Scopus)

Crynodeb

In this paper a method of adaptive selection of helper-objectives in evolutionary algorithms, which was previously applied to model problems only, is applied to generation of test cases for programming challenge tasks. The method is based on reinforcement learning. Experiments show that the proposed method performs equally well compared to the best helper-objectives selected by hand.

Iaith wreiddiol	Saesneg
Teitl	Proceedings of the IEEE Congress on Evolutionary Computation
Is-deitl	CEC 2013, Cancun, Mexico, June 20-23, 2013.
Cyhoeddwr	IEEE Press
Tudalennau	2245-2250
Nifer y tudalennau	6
ISBN (Argraffiad)	9781479904532, 1479904538
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1109/CEC.2013.6557836
Statws	Cyhoeddwyd - 20 Meh 2013
Cyhoeddwyd yn allanol	Ie
Digwyddiad	2013 IEEE Congress on Evolutionary Computation (CEC) - Cancun, Mecsico Hyd: 20 Meh 2013 → 23 Meh 2013

Cynhadledd

Cynhadledd	2013 IEEE Congress on Evolutionary Computation (CEC)
Gwlad/Tiriogaeth	Mecsico
Dinas	Cancun
Cyfnod	20 Meh 2013 → 23 Meh 2013

Mynediad at Ddogfen

10.1109/CEC.2013.6557836

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Dolen barhaus

Ffeiliau eraill a chysylltiadau

https://www.scopus.com/record/display.uri?eid=2-s2.0-84881607872&origin=resultslist

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@inproceedings{25119d924c61401c93852855ec2d58b4,

title = "Adaptive selection of helper-objectives for test case generation",

abstract = "In this paper a method of adaptive selection of helper-objectives in evolutionary algorithms, which was previously applied to model problems only, is applied to generation of test cases for programming challenge tasks. The method is based on reinforcement learning. Experiments show that the proposed method performs equally well compared to the best helper-objectives selected by hand.",

author = "Maxim Buzdalov and Arina Buzdalova",

year = "2013",

month = jun,

day = "20",

doi = "10.1109/CEC.2013.6557836",

language = "English",

isbn = "9781479904532",

pages = "2245--2250",

booktitle = "Proceedings of the IEEE Congress on Evolutionary Computation",

publisher = "IEEE Press",

address = "United States of America",

note = "2013 IEEE Congress on Evolutionary Computation (CEC) ; Conference date: 20-06-2013 Through 23-06-2013",

}

TY - GEN

T1 - Adaptive selection of helper-objectives for test case generation

AU - Buzdalov, Maxim

AU - Buzdalova, Arina

PY - 2013/6/20

Y1 - 2013/6/20

N2 - In this paper a method of adaptive selection of helper-objectives in evolutionary algorithms, which was previously applied to model problems only, is applied to generation of test cases for programming challenge tasks. The method is based on reinforcement learning. Experiments show that the proposed method performs equally well compared to the best helper-objectives selected by hand.

AB - In this paper a method of adaptive selection of helper-objectives in evolutionary algorithms, which was previously applied to model problems only, is applied to generation of test cases for programming challenge tasks. The method is based on reinforcement learning. Experiments show that the proposed method performs equally well compared to the best helper-objectives selected by hand.

UR - https://www.scopus.com/record/display.uri?eid=2-s2.0-84881607872&origin=resultslist

U2 - 10.1109/CEC.2013.6557836

DO - 10.1109/CEC.2013.6557836

M3 - Conference Proceeding (Non-Journal item)

SN - 9781479904532

SN - 1479904538

SP - 2245

EP - 2250

BT - Proceedings of the IEEE Congress on Evolutionary Computation

PB - IEEE Press

T2 - 2013 IEEE Congress on Evolutionary Computation (CEC)

Y2 - 20 June 2013 through 23 June 2013

ER -

Adaptive selection of helper-objectives for test case generation

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