Title :
Parsimonious classifiers for software quality assessment
Author :
Shin, Miyoung ; Goel, Amrit L. ; Ratanothayanon, Sunidaa ; Paul, Raymond A.
Author_Institution :
Kyungpook Nat. Univ., Daegu
Abstract :
Modeling to predict fault-proneness of software modules is an important area of research in software engineering. Most such models employ a large number of basic and derived metrics as predictors. This paper presents modeling results based on only two metrics, lines of code and cyclomatic complexity, using radial basis functions with Gaussian kernels as classifiers. Results from two NASA systems are presented and analyzed.
Keywords :
Gaussian processes; radial basis function networks; software fault tolerance; software metrics; software quality; Gaussian kernels; cyclomatic complexity; fault-proneness prediction; parsimonious classifiers; radial basis functions; software engineering; software metrics; software modules; software quality assessment; Kernel; Mathematical model; NASA; Neural networks; Predictive models; Software engineering; Software metrics; Software quality; System testing; Systems engineering and theory; Software quality; Classification; Parsimonious classifiers; Software metrics;
Conference_Titel :
High Assurance Systems Engineering Symposium, 2007. HASE '07. 10th IEEE
Conference_Location :
Plano, TX
Print_ISBN :
978-0-7695-3043-7
DOI :
10.1109/HASE.2007.75
