CRI: CI-New: Collaborative Research: NJR: A Normalized Java Resource

CRI：CI-New：协作研究：NJR：标准化 Java 资源

• 批准号: 1823227
• 负责人: Cristina Lopes
• 金额: $ 50万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-15 至 2022-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1823227&HistoricalAwards=false
• 关键词: CRI; CI; New; Collaborative; Research

Research in programming languages and software engineering has increasingly become a "big data" science ("Big Code") is which researchers want to use large code bases to experiment with new techniques. Specifically, Big Code will enable novel tools in areas such as security enhancers, bug finders, and code synthesizers. This project will build a community resource of 100,000 executable Java programs together with a set of working tools and an environment for conducting such research. This Normalized Java Resource (NJR) will lower the barrier to implementation of new tools, speed up research, and ultimately help advance research frontiers. Additionally, NJR can be the foundation of new courses on software tools that take advantage of Big Code. Finally, NJR can be the centerpiece of a discussion about better benchmark suites in general. The two investigators will work with collaborators from five countries. Researchers get significant advantages from using NJR. They can write scripts that base their new tool on NJR's already-working tools, and they can search NJR for programs with desired characteristics. They will receive the search result as a container that they can run either locally or on a cloud service. Additionally, they benefit from NJR's normalized representation of each Java program, which enables scalable running of tools on the entire collection. Finally, they will find that NJR's collection of programs is diverse because of the investigators' efforts to run clone detection and near-duplicate removal.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.

编程语言和软件工程的研究日益成为一门“大数据”科学（“大代码”），研究人员希望使用大型代码库来试验新技术。 具体来说，大代码将在安全增强器、错误查找器和代码合成器等领域启用新颖的工具。 该项目将建立一个包含 100,000 个可执行 Java 程序的社区资源以及一套工作工具和进行此类研究的环境。 这种规范化 Java 资源 (NJR) 将降低实施新工具的障碍，加快研究速度，并最终帮助推进研究前沿。 此外，NJR 可以成为利用大代码的软件工具新课程的基础。 最后，NJR 可以成为关于更好的基准测试套件的讨论的核心。 两名研究人员将与来自五个国家的合作者合作。研究人员通过使用 NJR 获得了显着的优势。 他们可以编写基于 NJR 已有工作工具的新工具的脚本，并且可以在 NJR 中搜索具有所需特性的程序。 他们将以容器形式接收搜索结果，可以在本地或云服务上运行。 此外，它们还受益于 NJR 对每个 Java 程序的标准化表示，这使得工具能够在整个集合上进行可扩展的运行。 最后，他们会发现 NJR 的程序集合是多样化的，因为研究人员努力运行克隆检测和近乎重复的删除。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的评估进行评估，被认为值得支持。影响审查标准。

项目成果

D-REX: Static Detection of Relevant Runtime Exceptions with Location Aware Transformer

D-REX：使用位置感知变压器静态检测相关运行时异常

• 发表时间: 2021-09
• 期刊: 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation
• 作者: Farima Farmahinifarahani; Yadong Lu
• 通讯作者: Yadong Lu