Practical and Explainable Analytics to Prevent Future Software Defects

实用且可解释的分析，以防止未来的软件缺陷

• 批准号: DE200100941
• 负责人: Dr Chakkrit Tantithamthavorn
• 金额: $ 27.58万
• 依托单位: Monash University
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Early Career Researcher Award
• 财政年份: 2020
• 资助国家: 澳大利亚
• 起止时间: 2020-03-02 至 2023-03-02
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DE200100941
• 关键词: Practical; Explainable; Analytics; Prevent; Future

This project aims to create technologies that enable software engineers to produce the highest quality software systems with the lowest costs, by preventing future defects in safety-critical systems that could result in death and disasters. Expected outcomes of this project include new theories, techniques, and analytics systems to assist software engineers accurately predict, explain, and prevent future software defects before they impact end users. This should provide significant benefits including accelerating the productivity of the software industry while preventing software defects in many critical domains including smart city and e-health applications.

该项目旨在创造技术，使软件工程师能够以最低的成本生产最高质量的软件系统，防止未来安全关键系统中可能导致死亡和灾难的缺陷。该项目的预期结果包括新的理论、技术和分析系统，以帮助软件工程师在软件缺陷影响最终用户之前准确地预测、解释和预防未来的软件缺陷。这应该会带来巨大的好处，包括加快软件行业的生产率，同时防止许多关键领域的软件缺陷，包括智能城市和电子健康应用程序。