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

CDA 9529766 Khoshgoftaar，Taghi M. Ganesan，Krishnamurthy 佛罗里达大西洋大学 软件工程研究实验室 拟议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，通过进行案例研究，探索神经网络架构和训练算法，提高软件质量模型的准确性。 (2)软件可测试性的度量和验证用于描述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。 案例研究，以解决这些问题的经验。 (3)模糊案例推理，通过使用工业案例研究数据开发原型系统，识别用于软件质量预测的模糊案例方法。 这些研究项目正在作出重大贡献， 描述了人们实际开发软件的方式 来自拥有专业开发组织的工业合作伙伴的大型系统数据。该设备包括五个高性能工程工作站，比其他可用的工作站快得多。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于上述研究项目至关重要。

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.