Efficient Safety Enforcement for Maude Programs via Program Specialization in the ÁTAME system

[EN] Program specialization is mainly recognized as a powerful technique for optimizing software systems. Nonetheless, it can also be productively employed in other application areas. This paper presents an assertion-guided program specialization methodology for efficiently imposing safety propertie...

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Detalles Bibliográficos
Autores: Alpuente Frasnedo, María|||0000-0002-9268-1178, Sapiña-Sanchis, Julia|||0000-0003-2994-6986, Ballis, D.
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/171423
Acceso en línea:https://riunet.upv.es/handle/10251/171423
Access Level:acceso abierto
Palabra clave:Safety properties
Assertions
Program transformation
Maude
LENGUAJES Y SISTEMAS INFORMATICOS
Descripción
Sumario:[EN] Program specialization is mainly recognized as a powerful technique for optimizing software systems. Nonetheless, it can also be productively employed in other application areas. This paper presents an assertion-guided program specialization methodology for efficiently imposing safety properties on software systems. The program specializer takes as input a set A of logical assertions that specifies the expected system behavior plus a software system that is modeled as a Maude program R that may violate some of the assertions in A. The outcome is a safe refinement R of R in which every system computation is a good run of R, i.e., it satisfies the assertions in A. The specialization technique has been fully automated in the ATAME system and ensures that no good run of R is removed from R, while the number of bad runs is reduced to zero. The efficiency and scalability of our technique is empirically demonstrated by means of a thorough experimental evaluation of the ATAME system, which shows fast specialization times and good performance of the computed specializations, even for large assertion sets.