CHS: SMALL: Collaborative Research: Adaptive Development Environments: Modeling and Supporting Cognitive Styles of Software Developers

CHS：SMALL：协作研究：自适应开发环境：建模和支持软件开发人员的认知风格

• 批准号: 2008089
• 负责人: Anita Sarma
• 金额: $ 25万
• 依托单位: Oregon State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2023-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2008089&HistoricalAwards=false
• 关键词: CHS; SMALL; Collaborative; Research; Adaptive

This research will investigate mechanisms to seamlessly support the different cognitive styles and information needs of software developers, such that development environments can model the developers' behavior and adapt to their individual needs. Software development is a notoriously complex endeavor that requires developers to use an environment where information is fragmented across different tools and repositories. Although integrated development environments may help, they are often inadequate in supporting developers' information needs. Major barriers are caused by development environments not adapting to the developers' cognitive styles and information needs. This project will advance the knowledge of software developers' behavior and transform software development tools to be more efficient and more inclusive to a wider population of software developers. It also addresses a fundamental issue concerning broader participation, that of individual differences in problem solving. Models and tools that accommodate these individual differences may help level the playing field. The methodology involves four stages: (1) conduct empirical studies to understand developers' information needs and cognitive styles, (2) build predictive models of developer behavior based on their cognitive styles, (3) create development environments that adapt to support developers' cognitive styles, and (4) evaluate the effectiveness of the predictive models and the adaptive environments. This work will generate a deep understanding of the impact of cognitive styles on how developers learn and make sense of the development history to place their work in the context of past and ongoing changes. It is novel in providing an integrated perspective on the broader set of history explorations in which programmers engage when they are programming as well as in leading to empirically validated predictive models that not only model how development activities are influenced by differences in cognitive styles, but also by the development task at hand. Key goals include the design and evaluation of a novel environment that not only allows developers to seamlessly explore different aspects of the development histories, but also adapts to support the individual needs of a developer. Extensive curated versions of the collected data will be developed and shared with the scientific community to promote additional research into the topic.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.

这项研究将研究无缝支持软件开发人员不同认知风格和信息需求的机制，以便开发环境可以模拟开发人员的行为并适应他们的个人需求。 软件开发是一项极其复杂的工作，要求开发人员使用信息分散在不同工具和存储库中的环境。尽管集成开发环境可能有所帮助，但它们通常不足以支持开发人员的信息需求。 主要障碍是由于开发环境不适应开发人员的认知方式和信息需求造成的。 该项目将增进对软件开发人员行为的了解，并转变软件开发工具，使其更高效、对更广泛的软件开发人员更具包容性。它还解决了涉及更广泛参与的一个基本问题，即解决问题时的个体差异。适应这些个体差异的模型和工具可能有助于创造公平的竞争环境。该方法包括四个阶段：（1）进行实证研究以了解开发人员的信息需求和认知风格，（2）根据开发人员的认知风格构建开发人员行为的预测模型，（3）创建适应支持开发人员认知的开发环境风格，(4) 评估预测模型和自适应环境的有效性。这项工作将深入了解认知风格对开发人员如何学习和理解开发历史的影响，从而将他们的工作置于过去和正在进行的变化的背景下。它的新颖之处在于，它为程序员在编程时参与的更广泛的历史探索提供了一个综合的视角，并产生了经过经验验证的预测模型，该模型不仅模拟了开发活动如何受到认知风格差异的影响，而且还模拟了开发活动如何受到认知风格差异的影响。通过手头的开发任务。 主要目标包括设计和评估新颖的环境，该环境不仅允许开发人员无缝地探索开发历史的不同方面，而且还能够适应支持开发人员的个人需求。将开发收集数据的广泛精选版本并与科学界共享，以促进对该主题的更多研究。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Visual Resume: Exploring developers’ online contributions for hiring

视觉简历：探索开发人员的在线招聘贡献

• DOI: 10.1016/j.infsof.2021.106633
• 发表时间: 2021
• 期刊: Information and Software Technology
• 影响因子: 3.9
• 作者: Kuttal, Sandeep Kaur;Chen, Xiaofan;Wang, Zhendong;Balali, Sogol;Sarma, Anita
• 通讯作者: Sarma, Anita

Designing for Cognitive Diversity: Improving the GitHub Experience for Newcomers

• DOI: 10.1109/icse-seis58686.2023.00007
• 发表时间: 2023-01
• 期刊: 2023 IEEE/ACM 45th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS)
• 作者: Í. Santos;J. F. Pimentel;I. Wiese;Igor Steinmacher;A. Sarma;M. Gerosa

How to Debug Inclusivity Bugs? A Debugging Process with Information Architecture

如何调试包容性错误？

• DOI: 10.1109/icse-seis55304.2022.9794009
• 发表时间: 2022
• 期刊: 2022 IEEE/ACM 44th International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS
• 作者: Guizani, Mariam;Steinmacher, Igor;Emard, Jillian;Fallatah, Abrar;Burnett, Margaret;Sarma, Anita
• 通讯作者: Sarma, Anita

Cognitive biases in software development

软件开发中的认知偏差

• DOI: 10.1145/3517217
• 发表时间: 2022
• 期刊: Communications of the ACM
• 影响因子: 22.7
• 作者: Chattopadhyay, Souti;Nelson, Nicholas;Au, Audrey;Morales, Natalia;Sanchez, Christopher;Pandita, Rahul;Sarma, Anita
• 通讯作者: Sarma, Anita

A new approach towards ensuring gender inclusive SE job advertisements

确保社会企业招聘广告性别包容的新方法

• DOI: 10.1145/3510458.3513016
• 发表时间: 2022
• 期刊: Proceedings of the2022 ACM/IEEE 44th International Conference on Software Engineering: Software Engineering in Society
• 作者: Kanij, Tanjila;Grundy, John;McIntosh, Jennifer;Sarma, Anita;Aniruddha, Gayatri
• 通讯作者: Aniruddha, Gayatri