CAREER: Analysis and Automation of Systematic Software Modifications

职业：系统软件修改的分析和自动化

• 批准号: 1460325
• 负责人: Miryung Kim
• 金额: $ 43.73万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2019-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1460325&HistoricalAwards=false
• 关键词: CAREER; Analysis; Automation; Systematic; Software

Software systems evolve. Developers must add features, fix bugs, and rewrite software systems to provide better functionality and higher performance. Existing systems also need to migrate to new hardware, computing environments, programming models, and libraries. There exist redundancies, inefficiencies, and error-proneness in the way that we evolve software systems today. In particular, recent empirical studies indicate that developers often apply similar but not identical changes to similar contexts. Making such systematic, repetitive program modifications is a tedious, manual, error-prone process.This project will investigate the extent and nature of repetitive program modifications and will design, build, and evaluate a novel approach, called SYDIT, which improves developer productivity in applying systematic changes. In this approach, developers no longer apply similar changes manually. Instead, developers provide the old and new version of selected code as an example change, and SYDIT will generalize a reusable, abstract, context-aware program transformation from it.(1) SYDIT will compute program differences between the old and new version of selected code and create a reusable edit script by identifying relevant data and control flow context and by abstracting the edits' content and position.(2) SYDIT will then automatically identify related candidate change locations and produce concrete, customized edits to each candidate.Incorporation with testing and change impact analysis will help developers validate suggested changes. SYDIT's new differential delta analysis will help developers understand the effect of ported changes in each target context.(3) Using a large corpus of project histories, this project will investigate the frequency and types of repetitive changes. The resulting data set will be used to evaluate SYDIT's accuracy and capability and to assess a productivity gain that can be achieved by SYDIT.The impact of this research will be substantially improved developer productivity in evolving large software systems. By helping developers apply changes to similar contexts exhaustively and inspect the effect of suggested changes, SYDIT will reduce errors of omission and relieve developers from tedious, error-prone hand editing. The empirical studies will expand our understanding of repetitive program changes during software evolution.

软件系统的发展。开发人员必须添加功能，修复错误并重写软件系统，以提供更好的功能和更高的性能。现有系统还需要迁移到新的硬件，计算环境，编程模型和库。我们今天发展软件系统的方式存在冗余，效率低下和错误参与性。特别是，最近的经验研究表明，开发人员通常对相似情况采用相似但不相同的变化。进行这种系统的，重复性的程序修改是一个繁琐的，手动的，容易出错的过程。本项目将研究重复性程序修改的程度和性质，并将设计，构建和评估一种称为Sydit的新颖方法，从而提高了开发人员在应用系统变化方面的生产力。 在这种方法中，开发人员不再手动应用类似的更改。取而代之的是，开发人员将所选代码的旧版本和新版本作为示例更改，而Sydit将概括可重复使用的，上下文感知的程序转换。（1）Sydit将对所选代码的旧版本和新版本之间的程序差异进行计算程序差异，并创建可重复使用的脚本，并通过确定相关的can​​dits and sydits'sydits'sydit'sydit'sydit'sydit。对每个候选人进行自定义编辑。进行测试和变化影响分析将有助于开发人员验证建议的更改。 Sydit的新差异三角洲分析将帮助开发人员了解每个目标上下文中移植变化的效果。（3）使用大量的项目历史语料库，该项目将研究重复性变化的频率和类型。最终的数据集将用于评估Sydit的准确性和能力，并评估可以通过Sydit实现的生产力增长。这项研究的影响将大大提高开发人员的生产力在不断发展的大型软件系统中。通过帮助开发人员详尽地将更改应用于相似的环境并检查建议更改的效果，Sydit将减少遗漏错误，并使开发人员免于乏味，容易出错的手部编辑。经验研究将扩大我们对软件演化过程中重复计划变化的理解。