CISE Research Instrumentation: Empirical Software Engineering Laboratory for Research in Software Engineering

CISE Research Instrumentation：用于软件工程研究的实证软件工程实验室

• 批准号: 9529766
• 负责人: Taghi Khoshgoftaar
• 金额: $ 4.98万
• 依托单位: Florida Atlantic University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-02-15 至 1998-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9529766&HistoricalAwards=false
• 关键词: CISE; Research; Instrumentation; Empirical; Software

CDA 9529766 Khoshgoftaar, Taghi M. Ganesan, Krishnamurthy Florida Atlantic University Empirical Software Engineering Laboratory for Research in Software Engineering The proposed Empirical Software Engineering Laboratory supports following research projects in software engineering. (1) Modeling of Software Quality Using Artificial Neural Networks for improving the accuracy of software quality models by conducting case studies exploring neural network architectures and training algorithms. (2) Measurement and Validation of Software Testability for characterizing relationships between testability and static software metrics, and for determining whether or not testability measurement can enhance software reliability prediction. Case studies to address these issues empirically are used. (3) Fuzzy Case-Based Reasoning for identifying fuzzy case-based methods for software quality prediction by developing prototype systems using industrial case study data. These research projects are making significant contributions by characterizing ways that people actually develop software by using data on large systems from industrial partners which have professional development organizations. The equipment includes five high performance engineering workstations that are significantly faster than others that are available. Purchased software includes measurement and modeling tools that are specifically applicable to the projects. Thus, the hardware and software of the Empirical Software Engineering Laboratory are critical to the above research projects.

CDA 9529766 Khoshgoftaar，Taghi M.Ganesan，Krishnamurthy佛罗里达大西洋大学软件工程研究经验软件工程实验室拟建的经验软件工程实验室支持以下软件工程研究项目。(1)使用人工神经网络进行软件质量建模通过案例研究探索神经网络体系结构和训练算法来提高软件质量模型的准确性。(2)软件可测试性度量和验证，用于刻画可测试性和静态软件度量之间的关系，并确定可测试性度量是否可以增强软件可靠性预测。本文采用案例研究的方法来解决这些问题。(3)利用工业案例数据开发原型系统，进行模糊案例推理，识别模糊案例软件质量预测方法。这些研究项目通过使用拥有专业开发组织的行业合作伙伴提供的大型系统上的数据来表征人们实际开发软件的方式，从而做出了重大贡献。该设备包括五个高性能工程工作站，它们比现有的其他工作站速度快得多。购买的软件包括专门适用于项目的测量和建模工具。因此，经验软件工程实验室的硬件和软件对上述研究项目至关重要。