.png){kind=icon}
.png){kind=icon}
Return
Efficient Execution of ATL Model Transformations Using Static Analysis and Parallelism
.png){kind=icon}
OA
AI
DOI：10.1109/TSE.2020.3011388.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Unified modeling language
Analytical models
Engines
Java
Scalability
Static analysis
Biological system modeling
Model transformation
MDE
ATL
performance
scalability
parallelization
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
5.6
Papers:
2.8K
Citations:
1.1W
Organization
View more organizations