SHF: Small: Supporting Regular Expression Testing, Search, Repair, Comprehension, and Maintenance

在软件开发中，正则表达式是一种常见的编程构造，用于许多目的，包括查询数据库、搜索文档、验证用户输入和解析文件。大多数编程语言都有标准库或对正则表达式处理的内置支持。尽管正则表达式经常出现在软件开发活动中，但它很容易出现编程错误。当正则表达式导致软件错误时，影响可能很严重，可能会导致数据损坏、安全漏洞、拒绝服务攻击或网站中断。该研究开发了测试、理解、重用和维护正则表达式的新技术，以提高开发人员的理解能力并减少相关错误。该方法是为正则表达式的测试套件、相似性度量和保持语义的转换制定覆盖标准。覆盖标准适用于正则表达式的自动机表示，并用于自动生成测试输入，以帮助开发人员充分测试正则表达式。相似性度量允许开发人员找到类似于有错误的正则表达式的正则表达式，并解释它们之间的行为差异。保留语义的转换增强了理解和维护，还支持正则表达式在语言之间的迁移。更广泛的影响主要来自减少与正则表达式相关的错误的目标，这为所有人创建了更可靠的软件。

In software development, regular expressions are a common programming construct used for many purposes, including querying databases, searching documents, validating user input, and parsing files. Most programming languages have standard libraries or built-in support for regular expression processing. Despite their frequent appearance in software development activities, regular expressions are prone to programming errors. When a regular expression is responsible for a software bug, the impact can be severe, possibly resulting in corrupted data, security vulnerabilities, denial of service attacks, or website outages. This research develops new techniques to test, understand, reuse, and maintain regular expressions, in an effort to improve developer comprehension and reduce related bugs.The approach is to develop coverage criteria for test suites, similarity metrics, and semantics-preserving transformations for regular expressions. The coverage criteria apply to the automata representation of the regular expression and are used to automatically generate test inputs to help developers adequately test regular expressions. The similarity metrics allow developers to find regular expressions that are similar to a buggy regular expression, as well as explain how the behavior differs among them. The semantics-preserving transformations enhance comprehension and maintenance, and also support the migration of regular expressions between languages.  The broader impacts come primarily from the goal of reducing bugs related to regular expressions, which creates more reliable software for all.