International Journal of Engineering and Technology

The ability of software in satisfying its functional requirements successfully is measured as software reliability, making it one of the most important characteristics of software quality. Improving software processes employed during the software development life cycle is essential to produce reliable software systems of assured quality. Software Reliability Growth Models (SRGMs) aid software engineers and managers in tracking and measuring the growth in reliability as software is being developed for quality assurance. Software quality is improved by continuously monitoring and controlling the software process. Statistical Process Control (SPC) is the application of statistical methods on software process data presented graphically to quickly and easily identify anomalies that enable the developer to address software failures. In this paper we proposed a SPC mechanism of control charts for time domain data using Burr Type III based on Non Homogenous Poisson Process (NHPP) and parameters are estimated by Maximum likelihood Estimation (MLE) method.