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The Comparative Study for Property of Learning Effect based on Software Reliability Model using Doubly Bounded Power Law Distribution  

Kim, Hee Cheul (남서울대학교 산업경영공학과)
Kim, Kyung-Soo (백석문화대학교 인터넷정보학부)
Publication Information
Convergence Security Journal / v.13, no.1, 2013 , pp. 71-78 More about this Journal
Abstract
In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The doubly bounded power law distribution model makeup Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.
Keywords
Learning Effects; NHPP; Doubly Bounded Power Law Distribution;
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