Osamu Mizuno,Michi Nakai
We have proposed a detection method of fault-prone modules based on the spam filtering technique, Fault-prone filtering. Fault- prone filtering is a method which uses the text classifier (spam filter) to classify source code modules in software. In this study, we propose an extension to use warning messages of a static code analyzer instead of raw source code. Since such warnings include useful information to detect faults, it is expected to improve the accuracy of fault-prone module prediction. From the result of experiment, it is found that warning messages of a static code analyzer are a good source of fault-prone filtering as the original source code. Moreover, it is discovered that it is more effective than the conventional method (that is, without static code analyzer) to raise the coverage rate of actual faulty modules.
Osamu Mizuno,Michi Nakai
Osamu Mizuno,Michi Nakai
659
Advances in Software Engineering
5
924923
8 pages
0
Can Faulty Modules be Predicted by Warning Messages of Static Code Analyzer?
http://www.hindawi.com/journals/ase/2012/924923/
2012
2012
Michi Nakai,Osamu Mizuno
We have proposed a detection method of fault-prone modules based on
the spam filtering technique, ``Fault-prone filtering.
Fault-prone filtering is a method that uses the text classifier
(spam filter) to classify source code modules in software.
In this study we propose a extension to use warning messages of a
static code analyzer instead of raw source code. Since such
warnings include useful information to detect faults, it is expected
to improve the accuracy of fault-prone module prediction.
From the result of experiment, it is found that warning messages of
a static code analyzer is a good source of fault-prone filtering.
Michi Nakai,Osamu Mizuno
Michi Nakai,Osamu Mizuno
Proc. of the Joint Conference of the 21th International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement (IWSM/MENSURA2011), Fast abstracts
652
11
Nara, Japan
18-21
1
Fault-prone Module Prediction By Filtering Warning Messages of Static Code Analyzer
2011