CAREER: Software Reliability and Security Risk Assessment: Modeling and Algorithms

职业：软件可靠性和安全风险评估：建模和算法

• 批准号: 1749635
• 负责人: Lance Fiondella
• 金额: $ 45.25万
• 依托单位: University of Massachusetts, Dartmouth
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1749635&HistoricalAwards=false
• 关键词: CAREER; Software; Reliability; Security; Risk

Consistent growth in the software sector of the US and world economies is a driving force for global prosperity and stability in the form of trillions of dollars in revenue and millions of rewarding careers. The spread of computing has increased society's dependence on reliable and secure software to ensure national security and system safety. Producing reliable and secure software is difficult because of its growing complexity, which poses serious challenges to many large companies and government organizations. Quantitative models to assess software reliability and security can assist organizations to deliver software systems on time and within budget.Intellectual merits related to the science of software reliability and security risk management include: multi-stage models to guide software acquisition and integration, multi-phase algorithms that combine numerical techniques to enhance the performance of model-fitting procedures without compromising stability, and an open source application to automatically apply software reliability methods, strengthen collaboration within the international research community, and promote education and dialogue between the research and practitioner communities. The open source application will crowdsource the contribution of models and algorithms, establishing a common platform for participants to implement results, hybridize modeling, and conduct algorithmic research.Multi-stage models will be applicable to scientific phenomenon and engineering activities that are too complex to accurately characterize with standard methods from probability. Multi-phase algorithms will be applicable to model-fitting in the many areas to which statistics is applied. The open source tool possesses the potential to hybridize results from the past 40 years as well as future discoveries, providing insight on how to leverage the international research community. The open architecture will provide a medium for collaboration and rapid research transition in a format that is immediately usable by the intended audience. The open source project is hosted through an Educator account of the GitHub online service (https://github.com/LanceFiondella/srt.core), including sample input data sets for the models developed, the source code of the open source tool, and educational materials. The major research findings will be published in open access journals and also made accessible on the project web site (https://sasdlc.org/lab/projects/srt.html). The project repository will be maintained as long as GitHub educator accounts remain a free online service.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.

美国和世界经济的软件领域的一致增长是全球繁荣和稳定的推动力，其收入和数百万美元的回报职业的形式是一万亿美元。计算的传播增加了社会对可靠和安全软件的依赖，以确保国家安全和系统安全。由于其日益增长的复杂性，生产可靠和安全的软件很困难，这对许多大型公司和政府组织构成了严重的挑战。评估软件可靠性和安全性的量化模型可以帮助组织按时和预算内交付软件系统。与软件可靠性和安全风险管理科学相关的智能绩效包括：指导软件获取和集成，多相算法的多阶段模型，这些算法，将数值技术融合在不包含模型构图的过程中的数值技术和构图构图的性能的多相关性能，并且国际研究界，并促进研究与从业者社区之间的教育和对话。开源应用程序将众包模型和算法的贡献，为参与者建立一个共同的平台，以实施结果，杂交建模和进行算法研究。多阶段模型将适用于科学现象和工程活动，这些活动太复杂，无法准确地与来自可能性的标准方法准确地表征。多相算法将适用于应用统计数据的许多领域的模型拟合。开源工具具有将过去40年以及未来发现的结果杂交结果的潜力，从而提供了有关如何利用国际研究界的见解。开放式体系结构将提供一种以预期受众立即使用的格式的合作和快速研究过渡的媒介。开源项目是通过GitHub在线服务（https://github.com/lancefiondella/srt.core）的教育者帐户托管的，包括开发的模型的示例输入数据集，开源工具的源代码和教育材料。主要的研究结果将在开放访问期刊上发布，也可以在项目网站（https://sasdlc.org/lab/projects/srt.html）上访问。只要GitHub教育者帐户仍然是免费的在线服务，该项目存储库将得到维护。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准通过评估来获得支持的。

项目成果

Online Optimal Release Time for Non-homogeneous Poisson Process Software Reliability Growth Model

非齐次泊松过程软件可靠性增长模型在线最优发布时间

• DOI: 10.1109/rams48030.2020.9153699
• 发表时间: 2020
• 期刊: Annual Reliability and Maintainability Symposium (RAMS 2020
• 作者: Nagaraju, Vidhyashree;Fiondella, Lance
• 通讯作者: Fiondella, Lance

Optimal Release Policy for Covariate Software Reliability Models

协变量软件可靠性模型的最优发布策略

• DOI: 10.1109/rams51473.2023.10088282
• 发表时间: 2023
• 期刊: Annual Reliability and Maintainability Symposium
• 作者: Yawlui, Ebenezer;Silva, Priscila;Nagaraju, Vidhyashree;Fiondella, Lance
• 通讯作者: Fiondella, Lance

A Covariate Software Reliability Model and Optimal Test Activity Allocation

协变量软件可靠性模型和最优测试活动分配

• DOI: 10.1016/j.jss.2020.110643
• 发表时间: 2021
• 期刊: International Conference on Reliability and Quality in Design
• 作者: Nagaraju, V.;Jayasinghe, C.;and Fiondella, L.
• 通讯作者: and Fiondella, L.

Connecting Software Reliability Growth Models to Software Defect Tracking

将软件可靠性增长模型与软件缺陷跟踪联系起来

• DOI: 10.1109/issre5003.2020.00022
• 发表时间: 2020
• 期刊: 2020 IEEE 31st International Symposium on Software Reliability Engineering (ISSRE
• 作者: Nafreen, Maskura;Luperon, Melanie;Fiondella, Lance;Nagaraju, Vidhyashree;Shi, Ying;Wandji, Thierry
• 通讯作者: Wandji, Thierry

A covariate software tool to guide test activity allocation

指导测试活动分配的协变量软件工具

• DOI: 10.1016/j.softx.2021.100909
• 发表时间: 2022
• 期刊: SoftwareX
• 影响因子: 3.4
• 作者: Aubertine, Jacob;Chen, Kenan;Nagaraju, Vidhyashree;Fiondella, Lance
• 通讯作者: Fiondella, Lance