Abstract
s the usage of software is getting increased day by day, there is a need for software reliability and for this several software reliability growth models exist that are capable of finding the occurrence of errors. It is also possible to find the reliability of time domain models based on order statistics with Non- Homogeneous Poisson Process (NHPP). The conditional failure rate is an important factor for software and order statistics can be used in various applications like characterization of problems, detecting outliers, linear estimation, study of system reliability, life testing, survival analysis, data compression and many others. Using Statistical Process Control (SPC), we can monitor when the software failures occurs, that helps in improving the reliability of software. In this paper, we proposed a control mechanism Pareto Type II model with an on order statistics based on NHPP and the observations are considered for time domain failure data. The unknown parameters are estimated using a well-known estimation method known as Maximum Likelihood Estimation (MLE). The model is analyzed using live data sets.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
