An Application of Model Seeding to Search-Based Unit Test Generation for Gson

Mitchell Olsthoorn; Pouria Derakhshanfar; Xavier Devroey

doi:10.1007/978-3-030-59762-7_17

An Application of Model Seeding to Search-Based Unit Test Generation for Gson

Mitchell Olsthoorn, Pouria Derakhshanfar, Xavier Devroey

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

Résumé

Model seeding is a strategy for injecting additional information in a search-based test generation process in the form of models, representing usages of the classes of the software under test. These models are used during the search-process to generate logical sequences of calls whenever an instance of a specific class is required. Model seeding was originally proposed for search-based crash reproduction. We adapted it to unit test generation using EvoSuite and applied it to Gson, a Java library to convert Java objects from and to JSON. Although our study shows mixed results, it identifies potential future research directions.

langue originale	Anglais
titre	Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings
rédacteurs en chef	Aldeida Aleti, Annibale Panichella
Editeur	Springer Science and Business Media Deutschland GmbH
Pages	239-245
Nombre de pages	7
ISBN (imprimé)	9783030597610
Les DOIs	https://doi.org/10.1007/978-3-030-59762-7_17
Etat de la publication	Publié - 2020
Modification externe	Oui
Evénement	12th International Symposium on Search-Based Software Engineering, SSBSE 2020 - Bari, Italie Durée: 7 oct. 2020 → 8 oct. 2020

Série de publications

Nom	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12420 LNCS
ISSN (imprimé)	0302-9743
ISSN (Electronique)	1611-3349

Une conférence

Une conférence	12th International Symposium on Search-Based Software Engineering, SSBSE 2020
Pays	Italie
La ville	Bari
période	7/10/20 → 8/10/20

Accès au document

10.1007/978-3-030-59762-7_17

Autres fichiers et liens

Link to publication in Scopus

Empreinte digitale Examiner les sujets de recherche de « An Application of Model Seeding to Search-Based Unit Test Generation for Gson ». Ensemble, ils forment une empreinte digitale unique.

Replication package of An Application of Model Seeding to Search-based Unit Test Generation for Gson
Derakhshanfar, P. (Créateur), Olsthoorn, M. (Créateur) & DEVROEY, X. (Créateur), Zenodo, 28 juil. 2020
DOI: 10.5281/zenodo.3963956
Ensemble de données

Contient cette citation

Olsthoorn, M., Derakhshanfar, P., & Devroey, X. (2020). An Application of Model Seeding to Search-Based Unit Test Generation for Gson. Dans A. Aleti, & A. Panichella (eds.), Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings (p. 239-245). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 12420 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-59762-7_17

Olsthoorn, Mitchell ; Derakhshanfar, Pouria ; Devroey, Xavier. / An Application of Model Seeding to Search-Based Unit Test Generation for Gson. Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings. Editeur / Aldeida Aleti ; Annibale Panichella. Springer Science and Business Media Deutschland GmbH, 2020. p. 239-245 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{4c314dc2988d4c43a416752f68f66e0d,

title = "An Application of Model Seeding to Search-Based Unit Test Generation for Gson",

abstract = "Model seeding is a strategy for injecting additional information in a search-based test generation process in the form of models, representing usages of the classes of the software under test. These models are used during the search-process to generate logical sequences of calls whenever an instance of a specific class is required. Model seeding was originally proposed for search-based crash reproduction. We adapted it to unit test generation using EvoSuite and applied it to Gson, a Java library to convert Java objects from and to JSON. Although our study shows mixed results, it identifies potential future research directions.",

keywords = "Case study, Model seeding, Search-based software testing",

author = "Mitchell Olsthoorn and Pouria Derakhshanfar and Xavier Devroey",

year = "2020",

doi = "10.1007/978-3-030-59762-7_17",

language = "English",

isbn = "9783030597610",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "239--245",

editor = "Aldeida Aleti and Annibale Panichella",

booktitle = "Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings",

address = "Germany",

note = "12th International Symposium on Search-Based Software Engineering, SSBSE 2020 ; Conference date: 07-10-2020 Through 08-10-2020",

}

Olsthoorn, M, Derakhshanfar, P & Devroey, X 2020, An Application of Model Seeding to Search-Based Unit Test Generation for Gson. Dans A Aleti & A Panichella (eds), Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), VOL. 12420 LNCS, Springer Science and Business Media Deutschland GmbH, p. 239-245, 12th International Symposium on Search-Based Software Engineering, SSBSE 2020, Bari, Italie, 7/10/20. https://doi.org/10.1007/978-3-030-59762-7_17

An Application of Model Seeding to Search-Based Unit Test Generation for Gson. / Olsthoorn, Mitchell; Derakhshanfar, Pouria; Devroey, Xavier.

Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings. Ed. / Aldeida Aleti; Annibale Panichella. Springer Science and Business Media Deutschland GmbH, 2020. p. 239-245 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol 12420 LNCS).

Résultats de recherche: Contribution dans un livre/un catalogue/un rapport/dans les actes d'une conférence › Article dans les actes d'une conférence/un colloque

TY - GEN

T1 - An Application of Model Seeding to Search-Based Unit Test Generation for Gson

AU - Olsthoorn, Mitchell

AU - Derakhshanfar, Pouria

AU - Devroey, Xavier

PY - 2020

Y1 - 2020

N2 - Model seeding is a strategy for injecting additional information in a search-based test generation process in the form of models, representing usages of the classes of the software under test. These models are used during the search-process to generate logical sequences of calls whenever an instance of a specific class is required. Model seeding was originally proposed for search-based crash reproduction. We adapted it to unit test generation using EvoSuite and applied it to Gson, a Java library to convert Java objects from and to JSON. Although our study shows mixed results, it identifies potential future research directions.

AB - Model seeding is a strategy for injecting additional information in a search-based test generation process in the form of models, representing usages of the classes of the software under test. These models are used during the search-process to generate logical sequences of calls whenever an instance of a specific class is required. Model seeding was originally proposed for search-based crash reproduction. We adapted it to unit test generation using EvoSuite and applied it to Gson, a Java library to convert Java objects from and to JSON. Although our study shows mixed results, it identifies potential future research directions.

KW - Case study

KW - Model seeding

KW - Search-based software testing

UR - http://www.scopus.com/inward/record.url?scp=85092921340&partnerID=8YFLogxK

U2 - 10.1007/978-3-030-59762-7_17

DO - 10.1007/978-3-030-59762-7_17

M3 - Conference contribution

AN - SCOPUS:85092921340

SN - 9783030597610

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 239

EP - 245

BT - Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings

A2 - Aleti, Aldeida

A2 - Panichella, Annibale

PB - Springer Science and Business Media Deutschland GmbH

T2 - 12th International Symposium on Search-Based Software Engineering, SSBSE 2020

Y2 - 7 October 2020 through 8 October 2020

ER -

Olsthoorn M, Derakhshanfar P, Devroey X. An Application of Model Seeding to Search-Based Unit Test Generation for Gson. Dans Aleti A, Panichella A, rédacteurs en chef, Search-Based Software Engineering - 12th International Symposium, SSBSE 2020, Proceedings. Springer Science and Business Media Deutschland GmbH. 2020. p. 239-245. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-030-59762-7_17