Improving Software Testing Education through Lightweight Explicit Testing Strategies and Feedback

该项目旨在通过设计工具和教学方法来帮助学生学习如何编写更好的软件测试，从而为国家利益服务。软件测试是计算机科学毕业生进入职场时的一项关键技能。拥有更好的软件测试技能的软件专业人员可能会产生更安全、更健壮、更少出错的软件。编写有效的软件测试是一个开放式的问题，学生们发现它非常具有挑战性。使用检查表已经被证明是帮助学生学习其他软件工程技能的有效实践。这个项目将调查检查表的使用，提供一个学生可以用来编写软件测试的过程。学生将学习如何编写软件测试并使用它们来评估他们开发的软件的质量。项目团队将开发一种软件工具，可以在软件上运行学生的测试，并提供实时提示和测试质量反馈。该项目还将从学生的学习成果和代码质量方面考察测试教育对学生的好处。这个项目的目标是帮助学生发展更好的软件测试技能，这样他们就能在计算工作中取得成功。该项目将开发新的数据驱动方法，为学生编写的软件测试生成自动测试反馈和提示。项目小组将进行一项纵向研究，以评估使用核对表和自动反馈对学生写试卷能力的影响，在三年内进行六次评估。该项目将解决三个研究问题：(1)检查表干预在多大程度上改善了学生的软件测试结果？(2)与不太严格的干预相比，自动化反馈对测试覆盖率和质量的好处是什么？(3)编写高质量的测试对学生的学习成果有什么影响？干预措施的影响将通过测试质量、实施质量、测试前和测试后测验分数之间的改进、使用调查对测试能力的自我评估以及学生在实验室和家庭作业的每个阶段所花费的时间来衡量。这个项目有可能对本科生学习软件测试的方式产生持久的影响。这个项目的结果将通过关注计算机科学教育的会议和期刊进行传播。项目团队将在GitHub上发布项目结果，包括工具、实验和教育材料。NSF IUSE: EHR计划支持研究和开发项目，以提高所有学生STEM教育的有效性。通过参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。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。

This project aims to serve the national interest by designing tools and pedagogy that will help students learn how to write better software tests. Software testing is a critical skill for computer science graduates when they enter the workforce. A software professional with better software testing skills is likely to produce more secure, more robust, and less error-prone software. Writing effective software tests is an open-ended problem that students find very challenging. The use of checklists has been shown to be an effective practice for helping students learn other software engineering skills. This project will investigate the use of checklists to provide a procedure that students can use to write software tests. Students will learn how to write software tests and use them to evaluate the quality of software they develop. The project team will develop a software tool that will run students’ tests on software and provide real-time hints and feedback on the quality of their tests. The project will also examine the benefits of testing education for students in terms of their learning outcomes and code quality. The goal of this project is to help students develop better software testing skills so that they will be successful in the computing workforce. This project will develop new data-driven methods for generating automated testing feedback and hints for software tests written by students. The project team will conduct a longitudinal study to assess the impact of using checklists and automated feedback on students’ ability to write tests using six evaluations over three years. The project will address three research questions: (1) To what extent does the checklist intervention improve students’ software testing outcomes? (2) What are the benefits of automated feedback on test coverage and quality as compared to less rigorous interventions? (3) What is the impact of writing high-quality tests on student learning outcomes? The impact of the interventions will be measured using test quality, implementation quality, improvement between pre- and post-test quiz scores, self-assessment of testing ability using a survey, and the time students spend working on each phase of their lab and homework assignments. The project has the potential to have a lasting impact on how undergraduate students learn software testing. The results of this project will be disseminated through conferences and journals that focus on computer science education. The project team will post project results including tools, experiments, and educational materials on GitHub. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.