A framework for genetic test-case generation for WS-BPEL compositions

Antonia Estero-Botaro; Antonio García-Domínguez; Juan José Domínguez-Jiménez; Francisco Palomo-Lozano; Inmaculada Medina-Bulo

doi:10.1007/978-3-662-44857-1_1

A framework for genetic test-case generation for WS-BPEL compositions

Antonia Estero-Botaro^*, Antonio García-Domínguez, Juan José Domínguez-Jiménez, Francisco Palomo-Lozano, Inmaculada Medina-Bulo

^*Corresponding author for this work

College of Engineering and Physical Sciences

Research output: Chapter in Book/Published conference output › Conference publication

Abstract

Search-based testing generates test cases by encoding an adequacy criterion as the fitness function that drives a search-based optimization algorithm. Genetic algorithms have been successfully applied in search-based testing: while most of them use adequacy criteria based on the structure of the program, some try to maximize the mutation score of the test suite.

This work presents a genetic algorithm for generating a test suite for mutation testing. The algorithm adopts several features from existing bacteriological algorithms, using single test cases as individuals and keeping generated individuals in a memory. The algorithm can optionally use automated seeding when producing the first population, by taking into account interesting constants in the source code.

We have implemented this algorithm in a framework and we have applied it to a WS-BPEL composition, measuring to which extent the genetic algorithm improves the initial random test suite. We compare our genetic algorithm, with and without automated seeding, to random testing.

Original language	English
Title of host publication	Testing software and systems
Subtitle of host publication	26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings
Editors	Mercedes G. Merayo, Edgardo Montes de Oca
Place of Publication	Berlin (DE)
Publisher	Springer
Pages	1-16
Number of pages	16
Volume	8763
ISBN (Electronic)	978-3-662-44857-1
ISBN (Print)	978-3-662-44856-4
DOIs	https://doi.org/10.1007/978-3-662-44857-1_1
Publication status	Published - 2014
Event	26th IFIP WG 6.1 International Conference - Madrid, Spain Duration: 23 Sept 2014 → 25 Sept 2014

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	8763
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	26th IFIP WG 6.1 International Conference
Abbreviated title	ICTSS 2014
Country/Territory	Spain
City	Madrid
Period	23/09/14 → 25/09/14

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10.1007/978-3-662-44857-1_1

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Estero-Botaro, A., García-Domínguez, A., Domínguez-Jiménez, J. J., Palomo-Lozano, F., & Medina-Bulo, I. (2014). A framework for genetic test-case generation for WS-BPEL compositions. In M. G. Merayo, & E. Montes de Oca (Eds.), Testing software and systems: 26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings (Vol. 8763, pp. 1-16). (Lecture Notes in Computer Science; Vol. 8763 ). Springer. https://doi.org/10.1007/978-3-662-44857-1_1

Estero-Botaro, Antonia ; García-Domínguez, Antonio ; Domínguez-Jiménez, Juan José et al. / A framework for genetic test-case generation for WS-BPEL compositions. Testing software and systems: 26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings. editor / Mercedes G. Merayo ; Edgardo Montes de Oca. Vol. 8763 Berlin (DE) : Springer, 2014. pp. 1-16 (Lecture Notes in Computer Science).

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title = "A framework for genetic test-case generation for WS-BPEL compositions",

abstract = "Search-based testing generates test cases by encoding an adequacy criterion as the fitness function that drives a search-based optimization algorithm. Genetic algorithms have been successfully applied in search-based testing: while most of them use adequacy criteria based on the structure of the program, some try to maximize the mutation score of the test suite.This work presents a genetic algorithm for generating a test suite for mutation testing. The algorithm adopts several features from existing bacteriological algorithms, using single test cases as individuals and keeping generated individuals in a memory. The algorithm can optionally use automated seeding when producing the first population, by taking into account interesting constants in the source code.We have implemented this algorithm in a framework and we have applied it to a WS-BPEL composition, measuring to which extent the genetic algorithm improves the initial random test suite. We compare our genetic algorithm, with and without automated seeding, to random testing.",

author = "Antonia Estero-Botaro and Antonio Garc{\'i}a-Dom{\'i}nguez and Dom{\'i}nguez-Jim{\'e}nez, {Juan Jos{\'e}} and Francisco Palomo-Lozano and Inmaculada Medina-Bulo",

year = "2014",

doi = "10.1007/978-3-662-44857-1_1",

language = "English",

isbn = "978-3-662-44856-4",

volume = "8763",

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Estero-Botaro, A, García-Domínguez, A, Domínguez-Jiménez, JJ, Palomo-Lozano, F & Medina-Bulo, I 2014, A framework for genetic test-case generation for WS-BPEL compositions. in MG Merayo & E Montes de Oca (eds), Testing software and systems: 26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings. vol. 8763, Lecture Notes in Computer Science, vol. 8763 , Springer, Berlin (DE), pp. 1-16, 26th IFIP WG 6.1 International Conference, Madrid, Spain, 23/09/14. https://doi.org/10.1007/978-3-662-44857-1_1

A framework for genetic test-case generation for WS-BPEL compositions. / Estero-Botaro, Antonia; García-Domínguez, Antonio; Domínguez-Jiménez, Juan José et al.
Testing software and systems: 26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings. ed. / Mercedes G. Merayo; Edgardo Montes de Oca. Vol. 8763 Berlin (DE): Springer, 2014. p. 1-16 (Lecture Notes in Computer Science; Vol. 8763 ).

Research output: Chapter in Book/Published conference output › Conference publication

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T1 - A framework for genetic test-case generation for WS-BPEL compositions

AU - Estero-Botaro, Antonia

AU - García-Domínguez, Antonio

AU - Domínguez-Jiménez, Juan José

AU - Palomo-Lozano, Francisco

AU - Medina-Bulo, Inmaculada

PY - 2014

Y1 - 2014

N2 - Search-based testing generates test cases by encoding an adequacy criterion as the fitness function that drives a search-based optimization algorithm. Genetic algorithms have been successfully applied in search-based testing: while most of them use adequacy criteria based on the structure of the program, some try to maximize the mutation score of the test suite.This work presents a genetic algorithm for generating a test suite for mutation testing. The algorithm adopts several features from existing bacteriological algorithms, using single test cases as individuals and keeping generated individuals in a memory. The algorithm can optionally use automated seeding when producing the first population, by taking into account interesting constants in the source code.We have implemented this algorithm in a framework and we have applied it to a WS-BPEL composition, measuring to which extent the genetic algorithm improves the initial random test suite. We compare our genetic algorithm, with and without automated seeding, to random testing.

AB - Search-based testing generates test cases by encoding an adequacy criterion as the fitness function that drives a search-based optimization algorithm. Genetic algorithms have been successfully applied in search-based testing: while most of them use adequacy criteria based on the structure of the program, some try to maximize the mutation score of the test suite.This work presents a genetic algorithm for generating a test suite for mutation testing. The algorithm adopts several features from existing bacteriological algorithms, using single test cases as individuals and keeping generated individuals in a memory. The algorithm can optionally use automated seeding when producing the first population, by taking into account interesting constants in the source code.We have implemented this algorithm in a framework and we have applied it to a WS-BPEL composition, measuring to which extent the genetic algorithm improves the initial random test suite. We compare our genetic algorithm, with and without automated seeding, to random testing.

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ER -

Estero-Botaro A, García-Domínguez A, Domínguez-Jiménez JJ, Palomo-Lozano F, Medina-Bulo I. A framework for genetic test-case generation for WS-BPEL compositions. In Merayo MG, Montes de Oca E, editors, Testing software and systems: 26th IFIP WG 6.1 International Conference, ICTSS 2014, Madrid, Spain, September 23-25, 2014. Proceedings. Vol. 8763. Berlin (DE): Springer. 2014. p. 1-16. (Lecture Notes in Computer Science). doi: 10.1007/978-3-662-44857-1_1

A framework for genetic test-case generation for WS-BPEL compositions

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