Risk chain prediction metrics for predicting fault proneness in Software Systems
نویسندگان
چکیده
منابع مشابه
Software Metrics Reduction for Fault-Proneness Prediction of Software Modules
It would be valuable to use metrics to identify the fault-proneness of software modules. However, few research works are on how to select appropriate metrics for fault-proneness prediction currently. We conduct a large-scale comparative experiment of nine different software metrics reduction methods over eleven public-domain data sets from the NASA metrics data repository. The Naive Bayes data ...
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Reliability of software counts on its fault-prone modules. This means that the less software consists of fault-prone units the more we may trust it. Therefore, if we are able to predict the number of fault-prone modules of software, it will be possible to judge the software reliability. In predicting software fault-prone modules, one of the contributing features is software metric by which one ...
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Most of the fault prediction studies have focused on the binary classification models that determine whether the input modules are fault-prone or not. More recently, several studies have shown that severity-based multi-classification models are more useful since they can predict the fault-proneness depending on the severity of the defects in the module. We present new severity-based prediction ...
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With the sharp rise in software dependability and failure cost, high quality has been in great demand. However, guaranteeing high quality in software systems which have grown in size and complexity coupled with the constraints imposed on their development has become increasingly difficult, time and resource consuming activity. Consequently, it becomes inevitable to deliver software that have no...
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ژورنال
عنوان ژورنال: IOSR Journal of Engineering
سال: 2012
ISSN: 2278-8719,2250-3021
DOI: 10.9790/3021-0281190195