CI-New: Collaborative Research: An Infrastructure that Combines Eye Tracking into Integrated Development Environments to Study Software Development and Program Comprehension

CI-New：协作研究：将眼动追踪结合到集成开发环境中以研究软件开发和程序理解的基础设施

• 批准号: 1730307
• 负责人: Bonita Sharif
• 金额: $ 23.72万
• 依托单位: Youngstown State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2019-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1730307&HistoricalAwards=false
• 关键词: CI; New; Collaborative; Research; Infrastructure

The software engineering research community is now using eye trackers to study how developers comprehend and develop software. Unfortunately, eye trackers have limited features and functionality, which need to be augmented to effectively study the behavior of software developers performing programming and contextual tasks. Eye tracking devices only allow scientists to study fixed, limited-size, stimuli (e.g., block of text or image). Studies normally require that the text fit on one screen (or page). There is very limited or no support to allow such things as scrolling through longer documents or switching back and forth between documents on a computer. While this is sufficient to study how people read one line of code or a sentence it is wholly inadequate to study how programmers attempt to comprehend or develop a large software system.The objective of the research is to address this limitation and drastically expand the types and size of stimuli that can be studied using an eye tracking device. In addition to supporting source code artifacts, it also supports artifacts such as stack overflow documents, bug reports, testing documents, and requirements. This enables software engineering researchers to conduct large-scale realistic eye-tracking studies seamlessly within a software development environment. This eye-tracking-enabled infrastructure for studying program comprehension has the potential to transform the way lab studies and field studies are designed and executed as it advances the state of the art in conducting eye tracking studies in software engineering. The infrastructure directly impacts society by paving the way to further improve IDEs to support the developer in various software engineering tasks through the various research projects it facilitates. The immediate impact is to facilitate controlled laboratory and field environments for a community of researchers. The research may lead to software development tools that incorporate eye-tracking as part of a more productive programming environment leading to higher quality software.

软件工程研究社区现在正在使用眼动仪来研究开发人员如何理解和开发软件。不幸的是，眼动仪的特性和功能是有限的，为了有效地研究软件开发人员执行编程和上下文任务的行为，需要对其进行增强。眼动追踪设备只允许科学家研究固定的、有限大小的刺激（例如，文本或图像块）。研究通常要求文本适合一个屏幕（或一页）。对于在计算机上滚动较长的文档或在文档之间来回切换等操作的支持非常有限或根本不支持。虽然这对于研究人们如何阅读一行代码或一个句子是足够的，但对于研究程序员如何试图理解或开发一个大型软件系统是完全不够的。这项研究的目的是解决这一限制，并大大扩大使用眼动追踪设备可以研究的刺激类型和大小。除了支持源代码工件之外，它还支持诸如堆栈溢出文档、错误报告、测试文档和需求之类的工件。这使得软件工程研究人员能够在软件开发环境中无缝地进行大规模逼真的眼球追踪研究。这种用于研究程序理解的眼动追踪基础设施有可能改变实验室研究和现场研究的设计和执行方式，因为它推动了软件工程中进行眼动追踪研究的艺术状态。基础设施为进一步改进ide铺平了道路，从而通过它所促进的各种研究项目来支持开发人员完成各种软件工程任务，从而直接影响社会。其直接影响是为研究人员群体提供了受控的实验室和现场环境。这项研究可能会导致软件开发工具，将眼球追踪作为更高效的编程环境的一部分，从而产生更高质量的软件。