Ponencia en Congreso:
Automatically identifying sufficient object builders from Module APIs

dc.contributor.authorPonzio, Pablo
dc.contributor.authorBengolea, Valeria
dc.contributor.authorPolitano, Mariano
dc.contributor.authorAguirre, Nazareno
dc.contributor.authorFrías, Marcelo
dc.date.accessioned2020-03-26T18:26:51Z
dc.date.available2020-03-26T18:26:51Z
dc.date.issued2019
dc.description.abstract"Various approaches to software analysis (e.g. test input generation, software model checking) require engineers to (manually) identify a subset of a module’s methods in order to drive the analysis. Given a module to be analyzed, engineers typically select a subset of its methods to be considered as object builders to define a so-called driver, that will be used to automatically build objects for analysis, e.g., combining them non-deterministically, randomly, etc. This requires a careful inspection of the module and its API, since both the relative exhaustiveness of the analysis (leaving important methods out may systematically avoid generating different objects), as well as its efficiency (the different bounded combinations of methods grows exponentially as the number of methods increases), are affected by the selection. We propose an approach for automatically selecting a set of builders from a module’s API, based on an evolutionary algorithm that favors sets of methods whose combinations lead to producing larger sets of objects. The algorithm also takes into account other characteristics of these sets of methods, trying to prioritize the selection of methods with less and simpler parameters. As the implementation of this evolutionary mechanism requires in principle handling and comparing large sets of objects, and this grows very quickly both in terms of space and running times, we employ an abstraction of sets of objects, called field extensions, that involves using the field values of the objects in the set instead of the actual objects, and enables us to effectively implement our mechanism. An experimental assessment on a benchmark of stateful classes shows that our approach can automatically identify sets of builders that are sufficient (can be used to create any instance of the module) and minimal (do not contain superfluous methods), in a reasonable time."en
dc.identifier.isbn978-3030-16-721-9
dc.identifier.issn0302-9743
dc.identifier.urihttp://ri.itba.edu.ar/handle/123456789/1919
dc.language.isoenen
dc.relationinfo:eu-repo/semantics/altIdentfier/doi/10.1007/978-3-030-16722-6_25
dc.subjectINTERFACES DE PROGRAMACION DE APLICACIONESes
dc.subjectINGENIERIA DE SOFTWAREes
dc.subjectALGORITMOS EVOLUTIVOSes
dc.subjectVERIFICACION DE SOFTWAREes
dc.titleAutomatically identifying sufficient object builders from Module APIsen
dc.typePonencias en Congresoses
dc.typeinfo:eu-repo/semantics/acceptedVersion
dspace.entity.typePonencia en Congreso
itba.description.filiationFil: Ponzio, Pablo. Universidad Nacional de Río Cuarto; Argentina.
itba.description.filiationFil: Ponzio, Pablo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Bengolea, Valeria. Universidad Nacional de Río Cuarto; Argentina.
itba.description.filiationFil: Politano, Mariano. Universidad Nacional de Río Cuarto; Argentina.
itba.description.filiationFil: Politano, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Aguirre, Nazareno. Universidad Nacional de Río Cuarto; Argentina.
itba.description.filiationFil: Aguirre, Nazareno. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.
itba.description.filiationFil: Frías, Marcelo. Instituto Tecnológico de Buenos Aires; Argentina.
itba.description.filiationFil: Frías, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina.

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