CI-ADDO-EN: Collaborative Research: Enhancing the srcML Infrastructure: A Mixed-Language Exploration, Analysis, and Manipulation Framework to Support Software Evolution

CI-ADDO-EN：协作研究：增强 srcML 基础设施：支持软件演进的混合语言探索、分析和操作框架

• 批准号: 1305292
• 负责人: Jonathan Maletic
• 金额: $ 60.09万
• 依托单位: Kent State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1305292&HistoricalAwards=false
• 关键词: CI; ADDO; EN; Collaborative; Research

The project is aimed at enhancing an existing infrastructure that supports software engineering research on very large bodies of source code. The srcML infrastructure currently includes a generic XML representation for a variety of programming languages, a robust and efficient parser for C/C++, and a limited set of tools to support analysis and manipulation of large bodies of source code. The infrastructure is currently being used by a wide number of researchers in the fields of software engineering and programming languages. It is also being directly applied to practical problems in a variety of industrial settings. The srcML infrastructure is open source and freely available to the public via a GPL license. Documentation for the infrastructure is available online and a number of other resources, including online tutorials, are under development. Additionally, tutorials on how to use the infrastructure to support various research efforts are planned for a number of software engineering conferences.The PIs plan to extend the current efficient and robust parsing and markup to a broader variety of widely used programming languages (namely Java and C#) and allows for the addition of new languages via a plugin grammar architecture. The current toolkit is being greatly expanded to support the exploration, analysis, and manipulation of very large code bases. The tools include such things as a static slicer, metrics computation, various static analysis tools, a fact extractor, a call graph generator, syntactic querying tools, and a syntactic differencing tool. Additionally, a set of tools to support the construction and application of transformation rules is being developed. Extending the infrastructure to a broader set of widely used languages enables researchers to investigate more production and commercial software. The enhancements to the srcML infrastructure can drastically reduce the entry cost for individuals to conduct research by enabling them to explore, analyze, and manipulate software in an extremely easy and flexible manner, thus allowing them more time to pursue novel and transformative research on software, software engineering, and software languages. The addition of analysis, transformation, and syntactic differencing tools enable unproblematic and flexible exploration of large code bases written in widely used programming languages.

该项目旨在加强现有的基础设施，支持对大量源代码的软件工程研究。 srcML基础设施目前包括用于各种编程语言的通用XML表示、用于C/C++的健壮且高效的解析器，以及用于支持分析和操纵大量源代码的有限工具集。 该基础设施目前正被软件工程和编程语言领域的大量研究人员使用。 它还被直接应用于各种工业环境中的实际问题。srcML基础设施是开源的，并通过GPL许可证免费向公众提供。 该基础设施的文档可在线获取，包括在线教程在内的其他一些资源正在开发中。 此外，还计划为一些软件工程会议提供关于如何使用基础设施支持各种研究工作的教程。PI计划将当前高效和强大的解析和标记扩展到更广泛的广泛使用的编程语言（即Java和C#），并允许通过插件语法架构添加新语言。 当前的工具包正在得到极大的扩展，以支持对非常大的代码库的探索、分析和操作。 这些工具包括静态切片器、度量计算、各种静态分析工具、事实提取器、调用图生成器、语法查询工具和语法差异工具。 此外，正在开发一套工具，以支持转换规则的构建和应用。 将基础设施扩展到更广泛的广泛使用的语言，使研究人员能够研究更多的生产和商业软件。 srcML基础设施的增强可以大大降低个人进行研究的入门成本，使他们能够以非常简单和灵活的方式探索，分析和操作软件，从而使他们有更多的时间来追求软件，软件工程和软件语言的新颖和变革性研究。 分析、转换和语法差异分析工具的增加使得能够毫无问题地灵活探索用广泛使用的编程语言编写的大型代码库。