An Impact of Linear Regression Models for Improving the Software Quality with Estimated Cost

Developing organizations are spends lots of money to finding the Errors and bugs. In this article, an application of defects removal effectiveness to improve the software quality and fault prone analysis, methods are finding the solution of parameters in linear regression models with cost estimating method. It describes the approach of quantitative quality management through defect removal effectiveness and statistical process control of cost analysis with historical project data. Software quality is going continuously monetary benefit to perform well management planning, and achieve a new height. In this methodology, Software quality model can make timely predictions of reliability indications; it's enabling to improve software development processes by target reducing the estimated cost for software products and improve the techniques for more effectively and efficiently.