SBIR Phase I: MuukTest Artificial Intelligence Powered Software Testing

这个小型企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力将使非技术用户能够创建完整和全面的软件测试自动化。此外，它将使成长中的软件公司能够以合理的成本更快地交付更高质量的产品。目前，这些公司将高达50%的资源用于质量保证（QA）和测试。本项目将开发软件测试的自动化流程。这个小型企业创新研究（SBIR）第一阶段项目将结合联合收割机符号推理算法、深度学习和强化学习模型，实现软件质量保证测试的自动化。这个项目要解决的两个问题是：（1）软件开发团队花费高达50%的时间来测试软件，（2）他们必须雇佣熟练的软件工程师来自动化这些测试。这项研究的目的是使用人工智能（AI）使软件质量保证测试更快，并使非技术工作者能够在不需要编码的情况下创建复杂的测试。该研究旨在通过（i）构建手动测试场景的基线，（ii）使用符号推理（SR）构建测试，（iii）结合深度学习，（iv）添加强化学习来生成测试，从而创建AI原型。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will enable non-technical users to create complete and comprehensive software test automation. Additionally, it will enable growing software companies to ship their products faster with higher quality at a reasonable cost. Currently, these companies spend up to 50% of their resources on quality assurance (QA) and testing. This project will develop an automated process for testing software.This Small Business Innovation Research (SBIR) Phase I project will combine symbolic reasoning algorithms, deep learning, and reinforcement learning models to automate software quality assurance testing. The two problems being addressed by this project are (1) software development teams spend up to 50% of their time testing software, and (2) they have to hire skilled software engineers to automate these tests. The objective of this research is to use artificial intelligence (AI) to make software quality assurance testing faster and enable non-technical workers to create sophisticated tests without the need to code. The proposed research aims to create an AI prototype by (i) building a baseline of manual test scenarios, (ii) building tests using symbolic reasoning (SR), (iii) incorporating deep learning, and (iv) adding reinforcement learning to generate tests.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.