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dc.contributor.author
Politano, Mariano  
dc.contributor.author
Bengolea, Valeria Susana  
dc.contributor.author
Molina, Facundo  
dc.contributor.author
Aguirre, Nazareno Matias  
dc.contributor.author
Frias, Marcelo Fabian  
dc.contributor.author
Ponzio, Pablo Daniel  
dc.date.available
2024-09-19T11:37:32Z  
dc.date.issued
2024-12  
dc.identifier.citation
Politano, Mariano; Bengolea, Valeria Susana; Molina, Facundo; Aguirre, Nazareno Matias; Frias, Marcelo Fabian; et al.; BEAPI: A tool for bounded exhaustive input generation from APIs; Elsevier Science; Science of Computer Programming; 238; 103153; 12-2024; 1-14  
dc.identifier.issn
0167-6423  
dc.identifier.uri
http://hdl.handle.net/11336/244599  
dc.description.abstract
Bounded exhaustive testing is a very effective technique for bug finding, which proposes to test a given program under all valid bounded inputs, for a bound provided by the developer. Existing bounded exhaustive testing techniques require the developer to provide a precise specification of the valid inputs. Such specifications are rarely present as part of the software under test, and writing them can be costly and challenging. To address this situation we propose BEAPI, a tool that given a Java class under test, generates a bounded exhaustive set of objects of the class solely employing the methods of the class, without the need for a specification. BEAPI creates sequences of calls to methods from the class' public API, and executes them to generate inputs. BEAPI implements very effective pruning techniques that allow it to generate inputs efficiently. We experimentally assessed BEAPI in several case studies from the literature, and showed that it performs comparably to the best existing specification-based bounded exhaustive generation tool (Korat), without requiring a specification of the valid inputs.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Elsevier Science  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Software Testing  
dc.subject
Automated Test Generation  
dc.subject
Bounded Exhaustive Testing  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
BEAPI: A tool for bounded exhaustive input generation from APIs  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2024-08-26T14:59:05Z  
dc.journal.volume
238  
dc.journal.number
103153  
dc.journal.pagination
1-14  
dc.journal.pais
Países Bajos  
dc.journal.ciudad
Amsterdam  
dc.description.fil
Fil: Politano, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina  
dc.description.fil
Fil: Bengolea, Valeria Susana. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina  
dc.description.fil
Fil: Molina, Facundo. Instituto Imdea Energia; España  
dc.description.fil
Fil: Aguirre, Nazareno Matias. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina  
dc.description.fil
Fil: Frias, Marcelo Fabian. University of Texas at El Paso; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina  
dc.description.fil
Fil: Ponzio, Pablo Daniel. Universidad Nacional de Río Cuarto; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba; Argentina  
dc.journal.title
Science of Computer Programming  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0167642324000765  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.scico.2024.103153