Software quality modeling using metrics of early artifacts

Software industries require reliability prediction for quality evaluation and resource planning. In early phase of software development, failure data is not accessible to conclude the reliability of software. However, early software fault prediction procedure provides a flexibility to predict the faults in early stage. In this paper, a software faults prediction model is proposed using BBN that focus on the structure of the software development process explicitly representing complex relationship of five influencing parameters (Techno-complexity, Practitioner Level, Creation Effort, Review Effort, and Urgency). In order to assess the constructed model, an empirical experiment has been performed, based on the data collected from software development projects used by an organization. The predicted fault ware found very near to the actual fault detected during testing.