We have proposed a detection method of fault-prone modules based on the spam filtering technique, ââ?¬Å?Fault-prone filtering.ââ?¬Â Faultprone\r\nfiltering is a method which uses the text classifier (spam filter) to classify source code modules in software. In this study, we\r\npropose an extension to use warning messages of a static code analyzer instead of raw source code. Since such warnings include\r\nuseful information to detect faults, it is expected to improve the accuracy of fault-prone module prediction. From the result of\r\nexperiment, it is found that warning messages of a static code analyzer are a good source of fault-prone filtering as the original\r\nsource code.Moreover, it is discovered that it is more effective than the conventional method (that is, without static code analyzer)\r\nto raise the coverage rate of actual faulty modules
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