SHF: Small: Personalizing API Documentation

应用程序编程接口（API），包括库、框架、工具包、软件开发工具包和Web服务，在大多数程序员的代码中使用。由于编程是一项人类活动，API的可用性对程序员的效率和生成的代码有很大的影响：API的可用性差已被证明会导致代码中的错误和安全漏洞，以及降低程序员的生产力。此外，今天的程序员必须一直学习新的API，因为他们切换项目或开始使用新的包或Web服务。关于API的可用性的一个长期存在但经常被忽视的抱怨是在文档中。为了有效，API文档必须告知具有不同专业水平的程序员如何正确有效地使用API。该项目将创建并经验性地评估一个系统，该系统自动估计使用API的知识需求，以及用户的需求和学习风格，以创建专注于用户需要知道的个性化文档。该项目有可能显著改善API的可用性和API学习，从而提高程序员的效率和生产力，并减少错误和安全缺陷，这将对所有计算机化系统产生重大影响。该项目涉及基础研究，以识别和表示程序员拥有的知识，以及程序员的学习风格，因为它与API有关，基于以用户为中心的研究和计算技术，包括挖掘软件库和自然语言处理。从这些来源，该系统将确定如何创建个性化的文档，以适当的格式提供正确的信息，而不需要文档作者做更多的工作。这项研究还将确定新的方法来支持面向过程的学习和修补，使它们都更有效。该研究包括与研究团队的工业合作伙伴合作，使用真实的和大型API，通过适当的用户研究来验证所有这些方法的有效性。该研究还旨在支持多样化的学习风格，这些风格通常是代表性不足的人群所青睐的风格，这些人群往往在软件中得不到支持。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。

Application programming interfaces (APIs), including libraries, frameworks, toolkits, software development kits and web services, are used throughout most programmers' code. Since programming is a human activity, the usability of the APIs has a big impact on the effectiveness of the programmer and the resulting code: poor usability of APIs has been shown to result in bugs and security holes in code, as well as to reduce the programmer's productivity. Further, today's programmers must be learning new APIs all the time, as they switch projects or start using new packages or web services. A longstanding, but often overlooked, complaint about the usability of APIs is in the documentation. To be effective, API documentation must inform programmers, who have varying levels of expertise, how to correctly and effectively use the API. This project will create and empirically evaluate a system that automatically estimates the knowledge needs to use an API, and the needs and learning style of the user, to create personalized documentation focused on what the user needs to know. The project has the potential to significantly improve API usability and API learning, which could improve programmer effectiveness and productivity, and reduce bugs and security flaws, which would have a significant impact on all computerized systems. This project involves fundamental research to identify and represent the knowledge that a programmer has, and programmers' learning styles, as it relates to APIs, based on user-centered studies and computational techniques including mining software repositories and natural language processing. From these sources, the system will identify how to create personalized documentation, which presents the right information in an appropriate format, without requiring the documentation writer to do much more work. The research will also identify new ways to support process-oriented learning and tinkering so they are both more effective. The research includes validating all of these for effectiveness through appropriate user studies using real and large APIs in collaboration with the research team's industrial partners. The research also aims to support diverse learning styles that are often the styles favored by underrepresented populations that tend to be unsupported in software.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.