REU Site: Science of Software

REU 网站：软件科学

• 批准号: 1559593
• 负责人: Christopher Parnin
• 金额: $ 35.54万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-02-01 至 2020-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1559593&HistoricalAwards=false
• 关键词: REU; Site; Science; Software

This project is for a new REU site at North Carolina State University. It is focused on training undergraduates in software engineering, particularly in skills related to data analytics. Data analytics has become increasingly important in how companies and researchers make decisions about improving the reliability and usability of software.The intention of the project is to give research exposure and training to a diverse group of undergraduate students. The project aims at building students' analytical skills as well as research skills with the goal of leading them toward a research career in future. The project will primarily recruit women and minorities through the STARs alliance and from non-PhD granting universities. The project covers various areas of software engineering including visualization and data manipulation in virtual reality, model-based reasoning, human aspects (e.g., eye tracking data), bug fixing, and software analytics which is a cross between software and data mining methods. The overall research theme will investigate how to take advantage of qualitative organizational knowledge which gives data its context and meaning integrated with quantitative data mining methods that support exploration of large and complex datasets. The project will encourage the students to disseminate their research findings through presentations as well as publishing in research venues.

该项目适用于北卡罗来纳州立大学的新 REU 站点。它专注于培训软件工程本科生，特别是与数据分析相关的技能。数据分析对于公司和研究人员如何做出有关提高软件可靠性和可用性的决策变得越来越重要。该项目的目的是为不同的本科生群体提供研究机会和培训。该项目旨在培养学生的分析能力和研究能力，以引导他们未来的研究生涯。该项目将主要通过 STAR 联盟和非博士学位授予大学招募女性和少数族裔。该项目涵盖软件工程的各个领域，包括虚拟现实中的可视化和数据操作、基于模型的推理、人类方面（例如眼动追踪数据）、错误修复以及软件分析（软件和数据挖掘方法之间的交叉）。总体研究主题将研究如何利用定性组织知识，这些知识赋予数据其背景和意义，并与支持探索大型复杂数据集的定量数据挖掘方法相结合。该项目将鼓励学生通过演讲以及在研究场所出版来传播他们的研究成果。