Manual and automated performance optimization of model transformation systems
Manual and automated performance optimization of model transformation systems
复制标题
模型转换系统的手动和自动性能优化
DOI：
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发表时间：
2010
期刊：
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通讯作者：
M. Asztalos
中科院分区：
文献类型：
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作者：
T. Mészáros;G. Mezei;T. Levendovszky;M. Asztalos
基于模型的开发是工业软件工程中几个问题最有前途的解决方案之一。图转换是一种经过验证的处理特定领域模型的方法。然而，为了被没有图形转换专家的领域专家使用，即使没有基于转换系统实现者可用的知识手动调整速度，它也必须是快速的。在本文中，我们比较了这种手动优化与基于顺序独立规则重叠左侧之间共享匹配的自动优化解决方案的性能。这在我们的场景中产生了11%的改进，尽管我们的原型实现最多只利用了两个规则之间的重叠，并且所分析的基准并不包含许多适用优化的情况。
Model-based development is one of the most promising solutions for several problems of industrial software engineering. Graph transformation is a proven method for processing domain-specific models. However, in order to be used by domain experts without graph transformation experts, it must be fast even if not tweaked for speed manually based on knowledge available only to the implementers of the transformation system. In this paper, we compare the performance of such manual optimizations with a solution using automated optimization based on sharing of matches between overlapping left-hand-sides of sequentially independent rules. This yields a 11% improvement in our scenario, although our prototypical implementation only exploits overlapping between, at most, two rules, and the analyzed benchmark does not contain many cases where the optimization is applicable.