Generation of tests for programming challenge tasks using evolution algorithms.

Maxim Buzdalov

doi:10.1145/2001858.2002086

Generation of tests for programming challenge tasks using evolution algorithms.

Maxim Buzdalov

ITMO University

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

10 Citations (Scopus)

Abstract

In this paper, an automated method for generation of tests in order to detect inefficient (slow) solutions for programming challenge tasks is proposed. The method is based on genetic algorithms.

The proposed method was applied to a task from the Internet problem archive - the Timus Online Judge. For this problem, none of the existed solutions passed the generated set of tests.

Original language	English
Title of host publication	GECCO '11
Subtitle of host publication	Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Editors	Natalio Krasnogor
Publisher	Association for Computing Machinery
Pages	763-766
Number of pages	4
ISBN (Print)	9781450306904, 145030690X
DOIs	https://doi.org/10.1145/2001858.2002086
Publication status	Published - 12 Jul 2011
Externally published	Yes
Event	GECCO 2011: The Genetic and Evolutionary Computation Conference - Ireland, United Kingdom of Great Britain and Northern Ireland Duration: 12 Jul 2011 → 16 Jul 2011

Conference

Conference	GECCO 2011: The Genetic and Evolutionary Computation Conference
Country/Territory	United Kingdom of Great Britain and Northern Ireland
City	Ireland
Period	12 Jul 2011 → 16 Jul 2011

Keywords

genetic algorithms
programming challenges
testing

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10.1145/2001858.2002086

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@inproceedings{09bc696e1788407a9cb57e5c46282894,

title = "Generation of tests for programming challenge tasks using evolution algorithms.",

abstract = "In this paper, an automated method for generation of tests in order to detect inefficient (slow) solutions for programming challenge tasks is proposed. The method is based on genetic algorithms.The proposed method was applied to a task from the Internet problem archive - the Timus Online Judge. For this problem, none of the existed solutions passed the generated set of tests.",

keywords = "genetic algorithms, programming challenges, testing",

author = "Maxim Buzdalov",

year = "2011",

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doi = "10.1145/2001858.2002086",

language = "English",

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editor = "Natalio Krasnogor",

booktitle = "GECCO '11",

publisher = "Association for Computing Machinery",

address = "United States of America",

note = "GECCO 2011: The Genetic and Evolutionary Computation Conference ; Conference date: 12-07-2011 Through 16-07-2011",

}

Buzdalov, M 2011, Generation of tests for programming challenge tasks using evolution algorithms. in N Krasnogor (ed.), GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. Association for Computing Machinery, pp. 763-766, GECCO 2011: The Genetic and Evolutionary Computation Conference, Ireland, United Kingdom of Great Britain and Northern Ireland, 12 Jul 2011. https://doi.org/10.1145/2001858.2002086

Generation of tests for programming challenge tasks using evolution algorithms. / Buzdalov, Maxim.
GECCO '11: Proceedings of the 13th annual conference companion on Genetic and evolutionary computation. ed. / Natalio Krasnogor. Association for Computing Machinery, 2011. p. 763-766.

Research output: Chapter in Book/Report/Conference proceeding › Conference Proceeding (Non-Journal item)

TY - GEN

T1 - Generation of tests for programming challenge tasks using evolution algorithms.

AU - Buzdalov, Maxim

PY - 2011/7/12

Y1 - 2011/7/12

N2 - In this paper, an automated method for generation of tests in order to detect inefficient (slow) solutions for programming challenge tasks is proposed. The method is based on genetic algorithms.The proposed method was applied to a task from the Internet problem archive - the Timus Online Judge. For this problem, none of the existed solutions passed the generated set of tests.

AB - In this paper, an automated method for generation of tests in order to detect inefficient (slow) solutions for programming challenge tasks is proposed. The method is based on genetic algorithms.The proposed method was applied to a task from the Internet problem archive - the Timus Online Judge. For this problem, none of the existed solutions passed the generated set of tests.

KW - genetic algorithms

KW - programming challenges

KW - testing

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U2 - 10.1145/2001858.2002086

DO - 10.1145/2001858.2002086

M3 - Conference Proceeding (Non-Journal item)

SN - 9781450306904

SN - 145030690X

SP - 763

EP - 766

BT - GECCO '11

A2 - Krasnogor, Natalio

PB - Association for Computing Machinery

T2 - GECCO 2011: The Genetic and Evolutionary Computation Conference

Y2 - 12 July 2011 through 16 July 2011

ER -

Generation of tests for programming challenge tasks using evolution algorithms.

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Keywords

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