SHF: Small: Knowledge Acceleration for Programming

SHF：小型：编程知识加速

• 批准号: 1814826
• 负责人: Aniket Kittur
• 金额: $ 50万
• 依托单位: Carnegie-Mellon University
• 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: 2018-06-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1814826&HistoricalAwards=false
• 关键词: SHF; Small; Knowledge; Acceleration; Programming

Programming is a critical skill that is vital for the future of work and having a globally competitive workforce. While there are many resources available for programmers to learn the details for writing code, an increasing amount of the time all programmers spend is not on writing code but instead on choosing among and adapting the growing amount of existing code and libraries available to them. One study reported that the most frequent programmer activity is searching for and trying to understand unfamiliar code, and more than 30% of all searches are for determining which APIs to use and how to use them. However, after each sense-making episode in which a programmer gains knowledge for themselves, their work is essentially lost, with no one else benefiting. Although there are many tools to help programmers find the answers, there are very few tools to help programmers make use of the knowledge gained performing the task, or share that knowledge with others. Capturing the work that programmers do in foraging, navigating, and organizing code-relevant information could significantly benefit later programmers interested in similar information. By referencing the captured knowledge from the resulting code, this can provide design rationale for why the API is used that way, which is one of the most often missing pieces of documentation. Furthermore, by making it easier for programmers to build off one another's knowledge, this proposed work has the potential to reduce common security vulnerabilities that arise from programmers not learning from others' mistakes, leading to more secure and correct code.In this research the PI aims to help the initial programmer collect, navigate, and organize knowledge to meet their goals, while capturing this knowledge and making it useful for later programmers with similar needs. This project studies the sense-making processes that programmers engage in while searching for and organizing knowledge for themselves, as well as studying which work that they do is useful for others. This project investigates how programmers spend their time searching for and making sense of complex information for themselves in order to accomplish their goals, including choosing among different APIs or methods within an API, adapting code snippets found on the Internet to meet their needs, or trying to learn unfamiliar code to fix an error or add a new feature. When performing tasks like these, programmers continually are making hypotheses, proposing questions, and discovering answers, both about the details as well as the meta-level questions such as the design rationale of why the decisions were made. These studies will inform the design, development, and evaluation of tools to support both the initial and later programmers. This research has the potential to significantly accelerate the speed at which programmers can create correct code by helping them gain relevant knowledge faster.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.

编程是一项至关重要的技能，对未来的工作和拥有具有全球竞争力的劳动力至关重要。虽然有许多资源可供程序员学习编写代码的细节，但所有程序员花在编写代码上的时间越来越多，而是在不断增加的现有代码和库中进行选择和调整。一项研究报告说，最常见的程序员活动是搜索并试图理解不熟悉的代码，超过30%的搜索是为了确定使用哪些api以及如何使用它们。然而，在程序员为自己获得知识的每个意义构建阶段之后，他们的工作基本上就失去了，其他人也没有受益。尽管有很多工具可以帮助程序员找到答案，但是很少有工具可以帮助程序员利用执行任务所获得的知识，或者与他人分享这些知识。获取程序员在搜索、导航和组织代码相关信息方面所做的工作，可以极大地帮助对类似信息感兴趣的后来的程序员。通过引用从结果代码中获取的知识，这可以提供以这种方式使用API的设计原理，这是文档中最常缺少的部分之一。此外，通过使程序员更容易地构建彼此的知识，这项建议的工作有可能减少由于程序员不从别人的错误中学习而产生的常见安全漏洞，从而导致更安全、更正确的代码。在这项研究中，PI旨在帮助最初的程序员收集、导航和组织知识以满足他们的目标，同时捕获这些知识并使其对具有类似需求的后续程序员有用。这个项目研究程序员在为自己搜索和组织知识时所参与的意义生成过程，以及研究他们所做的哪些工作对其他人有用。这个项目调查了程序员如何花费时间为自己搜索和理解复杂的信息，以实现他们的目标，包括在不同的API或API中的方法中进行选择，调整在互联网上找到的代码片段以满足他们的需求，或者尝试学习不熟悉的代码来修复错误或添加新功能。当执行这样的任务时，程序员不断地做出假设，提出问题，并发现答案，这些问题既涉及细节，也涉及元层面的问题，例如为什么做出决策的设计原理。这些研究将为工具的设计、开发和评估提供信息，以支持最初的和后来的程序员。这项研究有可能通过帮助程序员更快地获得相关知识来显著加快他们创建正确代码的速度。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识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

Crystalline: Lowering the Cost for Developers to Collect and Organize Information for Decision Making

• DOI: 10.1145/3491102.3501968
• 发表时间: 2022-02
• 期刊: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems
• 作者: Michael Xieyang Liu;A. Kittur;B. Myers

An Exploratory Study of Web Foraging to Understand and Support Programming Decisions

通过网络搜寻来理解和支持编程决策的探索性研究

• DOI: 10.1109/vlhcc.2018.8506517
• 发表时间: 2018
• 期刊: 2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC'18
• 作者: Hsieh, Jane;Liu, Michael Xieyang;Myers, Brad A.;Kittur, Aniket
• 通讯作者: Kittur, Aniket

UNAKITE: Support Developers for Capturing and Persisting Design Rationales When Solving Problems Using Web Resources

UNAKITE：支持开发人员在使用 Web 资源解决问题时捕获并坚持设计原理

• 发表时间: 2018
• 期刊: Workshop on Designing Technologies to Support Human Problem Solving at the IEEE Symposium on Visual Languages and Human-Centric Computing
• 作者: Liu, Michael Xieyang;Hahn, Nathan;Zhou, Angelina;Burley, Shaun;Deng, Emily;Kittur, Aniket;Myers, Brad A.
• 通讯作者: Myers, Brad A.

To Reuse or Not To Reuse?: A Framework and System for Evaluating Summarized Knowledge

重用还是不重用？：评估总结知识的框架和系统

• DOI: 10.1145/3449240
• 发表时间: 2021
• 期刊: Proceedings of the ACM on Human-Computer Interaction
• 作者: Liu, Michael Xieyang;Kittur, Aniket;Myers, Brad A.
• 通讯作者: Myers, Brad A.

Unakite: Scaffolding Developers' Decision-Making Using the Web

Unakite：使用 Web 为开发人员的决策提供脚手架

• DOI: 10.1145/3332165.3347908
• 发表时间: 2019
• 期刊: ACM Symposium on User Interface Software and Technology (UIST
• 作者: Liu, Michael Xieyang;Hsieh, Jane;Hahn, Nathan;Zhou, Angelina;Deng, Emily;Burley, Shaun;Taylor, Cynthia;Kittur, Aniket;Myers, Brad A.
• 通讯作者: Myers, Brad A.