Machine Learning Techniques to Predict Defects by using Testing Parameters

Abstract

Since ages, the software development plays a very crucial role in the arena of software engineering. An important part here is to believe that Artificial Intelligence and Machine Learning also started its way. In the process, several metrics were analyzed, composed and some predictions were made. These predictions are very much useful to analyze the defects based on machine learning. This can be done by using various system test parameters. We found certain techniques which are used to estimate the defects based on various aspects. These features are retrieved right from the inception of the software development. In this project, we present an advance view on wide variety of Machine Learning approaches, along with different capable areas of the defects by taking their parameters.