Efficient execution of ATL model transformations using static analysis and parallelism





Publicado en

Actas de las XXVII Jornadas de Ingeniería del Software y Bases de Datos (JISBD 2023)

Licencia Creative Commons


Although model transformations are considered to be the heart and soul of Model Driven Engineering (MDE), there are still several challenges that need to be addressed to unleash their full potential in industrial settings. Among other shortcomings, their performance and scalability remain unsatisfactory for dealing with large models, making their wide adoption difficult in practice. This paper presents A2L, a compiler for the parallel execution of ATL model transformations, which produces efficient code that can use existing multicore computer architectures, and applies effective optimizations at the transformation level using static analysis. We have evaluated its performance in both sequential and multi-threaded modes obtaining significant speedups with respect to current ATL implementations. In particular, we obtain speedups between 2.32x and 38.28x for the A2L sequential version, and between 2.40x and 245.83x when A2L is executed in parallel, with expected average speedups of 8.59x and 22.42x, respectively.


Acerca de Sánchez Cuadrado, Jesús

Palabras clave

Model Transformation, ATL, Optimization
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