BNSBASED SOFTWARE MODULES FAULT-PRONENESS RANKING MODEL

摘要

Software maintenance and testing engineers expect to target the maintenance resources to those modules that would otherwise have problems later. This paper focuses on building module faultproneness ranking model to distribute the limited resources effectively, with Bayesian Network as basic quantitative model. A case study validates the usability of Bayesian Network fault prediction model.