Risk chain prediction metrics in software engineering
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The Software Industry faces dynamic changes in business environments and the advancements of technologies, information technology (IT) projects are facing lots of challenges, and there is a need of applying systematic approaches to deal with the risks to ensure the project s success. This presents two atypical risk chain prediction metrics for barometer coupling and accord in software systems. Our aboriginal metric, Ideal Coupling between Object classes (ICBO), is based on the acclaimed CBO coupling metric, while the added metric, Ideal Lack of Cohesion on Methods (ILCOM5), is based on the LCO...
The Software Industry faces dynamic changes in business environments and the advancements of technologies, information technology (IT) projects are facing lots of challenges, and there is a need of applying systematic approaches to deal with the risks to ensure the project s success. This presents two atypical risk chain prediction metrics for barometer coupling and accord in software systems. Our aboriginal metric, Ideal Coupling between Object classes (ICBO), is based on the acclaimed CBO coupling metric, while the added metric, Ideal Lack of Cohesion on Methods (ILCOM5), is based on the LCOM5 accord metric. One advantage of the proposed risk chain prediction metrics is that they can be computed in a simpler way as compared to some of the structural metrics. We empirically advised ICBO and ILCOM5 for admiration fault proneness of classes in a ample accessible antecedent arrangement and compared these metrics with a host of absolute structural and risk chain prediction metrics for the aforementioned task.
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