BugBlitz-AI: An Intelligent QA Assistant
<|reference_start|>BugBlitz-AI: An Intelligent QA Assistant: The evolution of software testing from manual to automated methods has significantly influenced quality assurance (QA) practices. However, challenges persist in post-execution phases, particularly in result analysis and reporting. Traditional post-execution validation phases require manual intervention for result analysis and report generation, leading to inefficiencies and potential development cycle delays. This paper introduces BugBlitz-AI, an AI-powered validation toolkit designed to enhance end-to-end test automation by automating result analysis and bug reporting processes. BugBlitz-AI leverages recent advancements in artificial intelligence to reduce the time-intensive tasks of manual result analysis and report generation, allowing QA teams to focus more on crucial aspects of product quality. By adopting BugBlitz-AI, organizations can advance automated testing practices and integrate AI into QA processes, ensuring higher product quality and faster time-to-market. The paper outlines BugBlitz-AI's architecture, discusses related work, details its quality enhancement strategies, and presents results demonstrating its effectiveness in real-world scenarios.<|reference_end|>
@article{yao2024bugblitz-ai:,
    title={BugBlitz-AI: An Intelligent QA Assistant},
    author={Yi Yao and Jun Wang and Yabai Hu and Lifeng Wang and Yi Zhou and Jack
  Chen and Xuming Gai and Zhenming Wang and Wenjun Liu},
    journal={arXiv preprint arXiv:2406.04356},
    year={2024},
    archivePrefix={arXiv},
    eprint={2406.04356},
    primaryClass={cs.SE cs.AI}
}