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

Khoshgoftaar, Taghi M. Ganesan， Krishnamurthy佛罗里达大西洋大学研究软件工程的经验软件工程实验室提议的经验软件工程实验室支持软件工程中的以下研究项目。(1)利用人工神经网络进行软件质量建模，通过对神经网络架构和训练算法进行案例研究，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，用于描述可测试性与静态软件度量之间的关系，并用于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)基于模糊案例推理，利用工业案例研究数据开发原型系统，识别基于模糊案例的软件质量预测方法。这些研究项目通过描述人们实际通过使用来自拥有专业开发组织的工业合作伙伴的大型系统上的数据来开发软件的方式，做出了重大贡献。该设备包括五个高性能工程工作站，其速度明显快于其他可用的工作站。购买的软件包括特别适用于项目的测量和建模工具。因此，实证软件工程实验室的硬件和软件对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.