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Full-Text Articles in Physical Sciences and Mathematics
Mining Data From Multiple Software Development Projects, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya
Mining Data From Multiple Software Development Projects, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao, Naeem Seliya
Computer Science Faculty Publications
A large system often goes through multiple software project development cycles, in part due to changes in operation and development environments. For example, rapid turnover of the development team between releases can influence software quality, making it important to mine software project data over multiple system releases when building defect predictors. Data collection of software attributes are often conducted independent of the quality improvement goals, leading to the availability of a large number of attributes for analysis. Given the problems associated with variations in development process, data collection, and quality goals from one release to another emphasizes the importance of …
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
High-Dimensional Software Engineering Data And Feature Selection, Huanjing Wang, Taghi M. Khoshgoftaar, Kehan Gao
Computer Science Faculty Publications
Software metrics collected during project development play a critical role in software quality assurance. A software practitioner is very keen on learning which software metrics to focus on for software quality prediction. While a concise set of software metrics is often desired, a typical project collects a very large number of metrics. Minimal attention has been devoted to finding the minimum set of software metrics that have the same predictive capability as a larger set of metrics – we strive to answer that question in this paper. We present a comprehensive comparison between seven commonly-used filter-based feature ranking techniques (FRT) …
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
An Empirical Investigation Of Filter Attribute Selection Techniques For Software Quality Classification, Kehan Gao, Taghi M. Khoshgoftaar, Huanjing Wang
Computer Science Faculty Publications
Attribute selection is an important activity in data preprocessing for software quality modeling and other data mining problems. The software quality models have been used to improve the fault detection process. Finding faulty components in a software system during early stages of software development process can lead to a more reliable final product and can reduce development and maintenance costs. It has been shown in some studies that prediction accuracy of the models improves when irrelevant and redundant features are removed from the original data set. In this study, we investigated four filter attribute selection techniques, Automatic Hybrid Search (AHS), …