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Assessing Infinite Failure Software Reliability Model Using SPC (Statistical Process Control)  

Kim, Hee Cheul (남서울대학교 산업경영공학과)
Shin, Hyun Cheul (백석문화대학교 인터넷정보학부)
Publication Information
Convergence Security Journal / v.12, no.6, 2012 , pp. 85-92 More about this Journal
Abstract
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 infinite failure model and non-homogeneous Poisson Processes (NHPP). For someone making a decision about when to market software, the conditional failure rate is an important variables. The finite failure model 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 study. Statistical Process Control (SPC) can monitor the forecasting of software failure and there by 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 NHPP using mean value function of log Poission, log-linear and Parto distribution.
Keywords
Statistical Process Control (SPC); Non-Homogeneous Poisson Process; Finite Failure Model;
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Times Cited By KSCI : 1  (Citation Analysis)
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