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High-assurance and complex mission-critical software systems are heavily dependent on reliability of their underlying software applications. An early software fault prediction is a proven technique in achieving high software reliability. Prediction models based on software metrics can predict number of faults in software modules. Timely predictions of such(More)
Current software quality estimation models often involve using supervised learning methods to train a software quality classifier or a software fault prediction model. In such models, the dependent variable is a software quality measurement indicating the quality of a software module by either a risk-based class membership (e.g., whether it is fault-prone(More)