Synthesizing regular expressions from examples for introductory automata assignments

Mina Lee, Sunbeom So, Hakjoo Oh
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引用次数: 58

Abstract

We present a method for synthesizing regular expressions for introductory automata assignments. Given a set of positive and negative examples, the method automatically synthesizes the simplest possible regular expression that accepts all the positive examples while rejecting all the negative examples. The key novelty is the search-based synthesis algorithm that leverages ideas from over- and under-approximations to effectively prune out a large search space. We have implemented our technique in a tool and evaluated it with non-trivial benchmark problems that students often struggle with. The results show that our system can synthesize desired regular expressions in 6.7 seconds on the average, so that it can be interactively used by students to enhance their understanding of regular expressions.
从介绍自动机赋值的示例中综合正则表达式
我们提出了一种用于介绍性自动机赋值的综合正则表达式的方法。给定一组正例和反例,该方法自动合成最简单的正则表达式,接受所有正例,拒绝所有反例。关键的新颖之处在于基于搜索的合成算法,该算法利用过近似值和欠近似值的思想,有效地修剪出一个大的搜索空间。我们已经在一个工具中实现了我们的技术,并用学生经常遇到的重要基准问题对其进行了评估。结果表明,该系统平均在6.7秒内就能合成出所需要的正则表达式,可以供学生交互式使用,增强对正则表达式的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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