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Software reliability prediction classifies software modules as fault-prone modules and less fault-prone modules at the early age of software development. As to a difficult problem of choosing parameters for Support Vector Machine (SVM), this paper introduces Particle Swarm Optimization (PSO) to automatically optimize the parameters of SVM, and constructs a software reliability prediction model based...
Testing is an important and cost-intensive part of the software development life cycle. Defect prediction models try to identify error-prone components, so that these can be tested earlier or more in-depth, and thus improve the cost-effectiveness during testing. Such models have been researched extensively, but whether and when they are applicable in practice is still debated. The applicability depends...
We compare two types of model that have been used to predict software fault-proneness in the next release of a software system. Classification models make a binary prediction that a software entity such as a file or module is likely to be either faulty or not faulty in the next release. Ranking models order the entities according to their predicted number of faults. They are generally used to establish...
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