Framework para el Desarrollo de Software mediante Modularización Avanzada. 2da. Etapa

Permanent URI for this collection

https://repositorio.uai.edu.ar/handle/123456789/295

Browse

Browsing Framework para el Desarrollo de Software mediante Modularización Avanzada. 2da. Etapa by Author "Rodríguez Caldeira, Luciana"
  • Item
    A parallel tableau algorithm for BIG DATA verification
    (Universidad Nacional de La Matanza, 2020-10) Asteasuain, Fernando ; Rodríguez Caldeira, Luciana
    BIG DATA systems are becoming more and more present in our everyday life generating data and information that needs to be explored and analyzed. In this sense, formal verification tools and techniques must provide solutions to face with these new challenges since they been pointed out as one of the most needed software engineering activities to consolidate BIG DATA modern systems. In this work we present a parallel implementation of a tableau algorithm aiming to improve the performance of our formal verication scheme. The pursued objective behind this transformation is to adapt our framework to deal with BIG DATA systems.
  • Item
    An expressive and enriched specification language to synthezise behavior in BIG DATA systems
    (Universidad Nacional de Salta, 2021) Asteasuain, Fernando ; Rodríguez Caldeira, Luciana
    In this work we extend our behavioral speci_cation and controller synthesis framework FVS to deal with BIG DATA requirements. For one side, we enriched FVS expressive power by exhibiting how our language can handle uents and partial speci_cations. For the other side, we combined FVS with a parallel model checker in order to automatically obtain a controller given the behavior speci_cation. In this way, FVS can be presented as an attractive tool to formally verify and synthesize behavior for BIG DATA systems. Our approach is compared to other well known parallel tool analyzing a complex big data system.
  • Item
    Exploring parallel formal verification of BIG-DATA systems
    (Universidad de Palermo, 2021) Asteasuain, Fernando ; Rodríguez Caldeira, Luciana
    Software Engineering is trying to adapt its tools, mechanisms and techniques to cope with the challenges involved when developing BIG DATA software systems. In particular, formal verification in one of the areas that more urgently is required to step in. In this work we introduce two crucial aspects aiming to adapt FVS to cope with BIG Data requirements. For one side, FVS’s parallel algorithm is proved to be sound and correct. For the other side, we developed a compelling empirical validation of our approach, employing a communication protocol relevant in the industrial world within a context of parallel systems, introducing a load-balancer process and comparing several implementations.