Isao Sasano: Marker- Directed Optimization of UnCAL Graph Transformations
Isao Sasano: Marker- Directed Optimization of UnCAL Graph Transformations
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Isao Sasano：UnCAL 图转换的标记定向优化
DOI：
10.1007/978-3-642-32211-2_9
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
Keisuke Nakano
中科院分区：
文献类型：
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作者：
Soichiro Hidaka;Zhenjiang Hu;Kazuhiro Inaba;Hiroyuki Kato;Kazutaka Matsuda;Keisuke Nakano
Buneman等人提出了一个图代数称为UnCAL（非结构化的CALculus）的组合图转换的基础上结构递归，我们最近已经应用到模型转换。代数的组合性质极大地增强了变换的模块性。但是，组合转换之间生成的中间结果会导致开销。Buneman等人提出的融合规则，消除了中间结果，但辅助重写规则，使融合规则的实际应用是不明显的。UnCAL图模型包含了标记的概念，标记对应于结构递归中的递归函数调用。我们发现，有很多优化的机会，在重写级的基础上静态分析，特别是专注于标记。该分析可以安全地消除冗余函数调用。性能评估表明，它的实际有效性的非平凡的例子中的模型转换。
Buneman et al. proposed a graph algebra called UnCAL (Unstructured CALculus) for compositional graph transformations based on structural recursion, and we have recently applied to model transformations. The compositional nature of the algebra greatly enhances the modularity of transformations. However, intermediate results generated between composed transformations cause overhead. Buneman et al. proposed fusion rules that eliminate the intermediate results, but auxiliary rewriting rules that enable the actual application of the fusion rules are not apparent so far. UnCAL graph model includes the concept of markers, which correspond to recursive function call in the structural recursion. We have found that there are many optimization opportunities at rewriting level based on static analysis, especially focusing on markers. The analysis can safely eliminate redundant function calls. Performance evaluation shows its practical effectiveness for non-trivial examples in model transformations.