Artículo
Enhancing Search-based Testing with Testability Transformations for Existing APIs
Fecha de publicación:
01/2022
Editorial:
Association for Computing Machinery
Revista:
ACM Transactions on Software Engineering and Methodology
ISSN:
1049-331X
Idioma:
Inglés
Tipo de recurso:
Artículo publicado
Clasificación temática:
Resumen
Search-based software testing (SBST) has been shown to be an effective technique to generate test cases automatically. Its effectiveness strongly depends on the guidance of the fitness function. Unfortunately, a common issue in SBST is the so-called flag problem, where the fitness landscape presents a plateau that provides no guidance to the search. In this article, we provide a series of novel testability transformations aimed at providing guidance in the context of commonly used API calls (e.g., strings that need to be converted into valid date/time objects). We also provide specific transformations aimed at helping the testing of REST Web Services. We implemented our novel techniques as an extension to EvoMaster, an SBST tool that generates system-level test cases. Experiments on nine open-source REST web services, as well as an industrial web service, show that our novel techniques improve performance significantly.
Palabras clave:
REST-API
,
SWAGGER
,
OPENAPI
,
MIO
Archivos asociados
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Identificadores
Colecciones
Articulos(ICC)
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Articulos de INSTITUTO DE INVESTIGACION EN CIENCIAS DE LA COMPUTACION
Citación
Arcuri, Andrea; Galeotti, Juan Pablo; Enhancing Search-based Testing with Testability Transformations for Existing APIs; Association for Computing Machinery; ACM Transactions on Software Engineering and Methodology; 31; 1; 1-2022; 1-34
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