论文标题
属性语法中语义动作的综合
Synthesis of Semantic Actions in Attribute Grammars
论文作者
论文摘要
属性语法允许语义行动与无上下文语法的生产规则相关，从而提供了一种简单而有效的形式主义来定义语言的语义。但是，起草语义动作可能很棘手，并且会大大消耗开发者时间。在这项工作中，我们提出了一种综合方法，以自动从将字符串与其含义相关联的示例中推断出语义动作。我们还提出了一个新的覆盖率指标，派生覆盖范围。我们使用它来构建一个采样器，以有效并自动绘制字符串以驱动合成引擎。我们将自己的想法纳入工具，Panini，并在十二个基准上进行经验评估，包括向前的差异引擎，Java字节码子集的解释器以及C语言的迷你编译器至两次编码。我们的结果表明，Panini随着要合成的动作数量和无上下文语法的大小而表现得很好，显着超过了简单的基线。
Attribute grammars allow the association of semantic actions to the production rules in context-free grammars, providing a simple yet effective formalism to define the semantics of a language. However, drafting the semantic actions can be tricky and a large drain on developer time. In this work, we propose a synthesis methodology to automatically infer the semantic actions from a set of examples associating strings to their meanings. We also propose a new coverage metric, derivation coverage. We use it to build a sampler to effectively and automatically draw strings to drive the synthesis engine. We build our ideas into our tool, PANINI, and empirically evaluate it on twelve benchmarks, including a forward differentiation engine, an interpreter over a subset of Java bytecode, and a mini-compiler for C language to two-address code. Our results show that PANINI scales well with the number of actions to be synthesized and the size of the context-free grammar, significantly outperforming simple baselines.
