2010
DOI: 10.5120/1584-2124
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Fault Prediction Model by Fuzzy Profile Development of Reliability Relevant Software Metrics

Abstract: This paper presents a fault prediction model using reliability relevant software metrics and fuzzy inference system. For this a new approach is discussed to develop fuzzy profile of software metrics which are more relevant for software fault prediction. The proposed model predicts the fault density at the end of each phase of software development using relevant software metrics. On the basis of fault density at the end of testing phase, total number of faults in the software is predicted. The model seems to us… Show more

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Cited by 14 publications
(11 citation statements)
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“…Incidentally very few works are available in this area (Jiang et al (2007); Kim et al (2013); Mohan et al (2011);Yadav et al 2012Yadav et al , 2014Mohanta et al 2010;Cheung et al 2008;Pandey andGoyal 2009, 2010;Kumar and Misra 2008;Smidts et al 1998;Tripathi and Mall 2005;Fenton et al 2008;Xie et al 1999) compared to the SRGMs based on failure data gathered during testing phase. Among these models some are based on fuzzy logic (Yadav et al 2012(Yadav et al , 2014Pandey andGoyal 2009, 2010;Kumar and Misra 2008).…”
Section: Introductionmentioning
confidence: 97%
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“…Incidentally very few works are available in this area (Jiang et al (2007); Kim et al (2013); Mohan et al (2011);Yadav et al 2012Yadav et al , 2014Mohanta et al 2010;Cheung et al 2008;Pandey andGoyal 2009, 2010;Kumar and Misra 2008;Smidts et al 1998;Tripathi and Mall 2005;Fenton et al 2008;Xie et al 1999) compared to the SRGMs based on failure data gathered during testing phase. Among these models some are based on fuzzy logic (Yadav et al 2012(Yadav et al , 2014Pandey andGoyal 2009, 2010;Kumar and Misra 2008).…”
Section: Introductionmentioning
confidence: 97%
“…Yadav et al (2014) have proposed a fuzzy logic based model for predicting software defect density indicator at requirement, design and coding phase using reliability relevant software metrics. Pandey and Goyal (2010), have mentioned about fuzzy profiles of the RRSMs. They have considered two types of profiles: linear and logarithmic.…”
Section: Introductionmentioning
confidence: 98%
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