Prediction of defects returning back to test engineers in data center stability testing using machine learning techniques

Abstract

In emerging IT industry, development of product involves quality validation by testing the product, each fault (known as defect) undergoes various stages until it gets closed in the system. In the paper we discuss the life cycle of the defect to understand the various stages of the defect. Using Machine learning techniques, we could predict whether the defect will be back to submitter for clarification as need information state or the issue is fixed. In this paper we will discuss the machine learning techniques for predicting the defect back to tester for need information state and the method of accuracy in prediction.