期刊名称：International Journal of Computer Science, Engineering and Applications (IJCSEA)
印刷版ISSN：2231-0088
电子版ISSN：2230-9616
出版年度：2011
卷号：1
期号：4
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：There are many software reliability models that are based on the times of occurrences of errors in the debugging of software. It is shown that it is possible to do asymptotic likelihood inference for software reliability models based on order statistics or Non-Homogeneous Poisson Processes (NHPP), with asymptotic confidence levels for interval estimates of parameters. In particular, interval estimates from these models are obtained for the conditional failure rate of the software, given the data from the debugging process. The data can be grouped or ungrouped. For someone making a decision about when to market software, the conditional failure rate is an important parameter. Order statistics are used in a wide variety of practical situations. Their use in characterization problems, detection of outliers, linear estimation, study of system reliability, life-testing, survival analysis, data compression and many other fields can be seen from the many books. Statistical Process Control (SPC) can monitor the forecasting of software failure and thereby contribute significantly to the improvement of software reliability. Control charts are widely used for software process control in the software industry. In this paper we proposed a control mechanism based on order statistics of cumulative quantity between observations of time domain failure data using mean value function of Half Logistics Distribution (HLD) based on NHPP.
关键词：Order Statistics; Statistical Process Control (SPC); Half Logistics Distribution (HLD); NHPP
