Collaborative Research: CCRI: New: A Software Refactoring Community Infrastructure

软件重构通过重组现有代码和减少技术债务，在维护高质量软件方面发挥着至关重要的作用。尽管在过去20年中有超过5,000名作者发表了重构论文，但重构研究人员、学生和社区新成员缺乏公开可用的重构基准、工具和数据集。他们必须经常从头开始复制现有的重构研究--这浪费了时间、精力，并对有效性造成了威胁。该项目的创新之处在于创建和传播与软件重构相关的构件和在线工具的存储库，使重构成为一种服务，足以支持严格的经验性研究和实验，在广泛的研究人员、教育工作者、软件工程师和STEM研究人员社区中检测、区分优先级、修复、测试和记录软件质量问题。该项目的影响涉及重大的经济影响问题：大型软件公司每年花费数百万美元通过重构减少技术债务。公开发布的基础设施将支持将重构研究转化为实践，并将使STEM研究人员能够更好地维护他们的软件原型，因为这些原型不可避免地会腐烂。拟议的基础设施REFCRI将成为许多大学软件工程课程改革的催化剂，以强调重构的真实例子，并将为实践者提供大量的教育资源。调查人员将在该平台上组织研讨会，以促进社区的繁荣。调查人员将通过数据预处理技术管理一个重构数据集的存储库，以(I)清理数据，(Ii)检查其覆盖面和多样性。该项目的团队将发布一个API，允许重构社区轻松上传数据集、重构教学示例/教程、工具和出版物。这些数据集将作为基准，使研究人员能够验证新工具，并使软件工程领域能够进行新的经验性研究。这些数据集将提供现实的培训范例和工具，以加强将重构融入软件工程课程，并将作为从业者的巨大教育资源。调查人员将集成和协调(基于Kubernetes)覆盖重构整个生命周期的多个工具，方法是将现有工具的输入/输出自动转换为通用数据处理格式，并将工具打包为Docker图像。它们将使现有的重构工具易于配置、执行和集成。REFCRI将重新实现几个重构工具，来自文件和存储库，作为云中的服务。调查人员将首先自动挖掘开源开发人员手动应用的数百万个重构示例，然后他们将使用它们逐个推荐和合成新的重构，以支持STEM社区广泛使用的Python和其他数据科学语言。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Software Refactoring plays a crucial role in maintaining high-quality software by re-structuring existing code and reducing technical debt. Despite more than 5,000 authors publishing refactoring papers in the last two decades, refactoring researchers, students, and new community members lack publicly available refactoring benchmarks, tools, and datasets. They must frequently replicate existing refactoring research from scratch – this wastes time, effort, and introduces threats to validity. The project's novelties are to create and disseminate a repository of software refactoring-related artifacts and online tools, to enable refactoring as a service, sufficient to support rigorous empirical studies and experiments with the detection, prioritization, repair, testing, and documentation of software quality issues across a broad community of researchers, educators, software engineers, and STEM researchers. The project's impacts relate to issues of great economic impact: large software companies spend millions of dollars yearly to reduce the technical debt through refactoring. The publicly-released infrastructure will support the transition of refactoring research into practice and will enable STEM researchers to better maintain their software prototypes as these inevitably decay. The proposed infrastructure REFCRI will be a catalyst for revamping software engineering courses at many universities to emphasize real-world examples of refactoring and will offer tremendous education resources for practitioners. The investigators will organize workshops on the platform to foster a thriving community.The investigators will curate a repository of refactoring data sets via data pre-processing techniques to (i) clean the data, and (ii) check its coverage and diversity. The team of this project will release an API to allow the refactoring community to easily upload datasets, refactoring teaching examples/tutorials, tools, and publications. The data sets will serve as benchmarks that enable researchers to validate new tools and will enable new empirical studies in the field of software engineering. The data sets will provide realistic training examples and tools to enhance the integration of refactoring into software engineering curricula and will serve as a tremendous educational resource for practitioners. The investigators will integrate and orchestrate (based on Kubernetes) multiple tools covering the whole lifecycle of refactoring by automatically transforming the inputs/outputs of existing tools into generic data processing formats and packaging tools as Docker images. They will make existing refactoring tools easy to configure, execute, and integrate. REFCRI will re-implement several refactoring tools, from papers and repositories, as services in the cloud. The investigators will first automatically mine millions of examples of refactorings that open-source developers applied manually and then they will use them to recommend and synthesize new refactorings-by-example to support Python and other data science languages widely used by the STEM community.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.