Abstract
We have investigated through several experiments the differences in the fault-prone module prediction accuracy caused by the differences in the constituent code clone metrics of the prediction model. In the previous studies, they use one or more code clone metrics as independent variables to build an accurate prediction model. While they often use the clone detection method proposed by Kamiya et al. to calculate these metrics, the effect of the detection method on the prediction accuracy is not clear. In the experiment, we built prediction models using a dataset collected from an open source software project. The result suggests that the prediction accuracy is improved, when clone metrics derived from the various clone detection tool are used.
| Original language | English |
|---|---|
| Title of host publication | 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering, SANER 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 15-16 |
| Number of pages | 2 |
| ISBN (Electronic) | 9781509018550 |
| DOIs | |
| Publication status | Published - May 20 2016 |
| Event | 10th International Workshop on Software Clones, IWSC 2016 - Osaka, Japan Duration: Mar 15 2016 → … |
Other
| Other | 10th International Workshop on Software Clones, IWSC 2016 |
|---|---|
| Country | Japan |
| City | Osaka |
| Period | 3/15/16 → … |
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All Science Journal Classification (ASJC) codes
- Software
Cite this
Assessing the differences of clone detection methods used in the fault-prone module prediction. / Tsunoda, Masateru; Kamei, Yasutaka; Sawada, Atsushi.
2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering, SANER 2016. Institute of Electrical and Electronics Engineers Inc., 2016. p. 15-16 7476788.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Assessing the differences of clone detection methods used in the fault-prone module prediction
AU - Tsunoda, Masateru
AU - Kamei, Yasutaka
AU - Sawada, Atsushi
PY - 2016/5/20
Y1 - 2016/5/20
N2 - We have investigated through several experiments the differences in the fault-prone module prediction accuracy caused by the differences in the constituent code clone metrics of the prediction model. In the previous studies, they use one or more code clone metrics as independent variables to build an accurate prediction model. While they often use the clone detection method proposed by Kamiya et al. to calculate these metrics, the effect of the detection method on the prediction accuracy is not clear. In the experiment, we built prediction models using a dataset collected from an open source software project. The result suggests that the prediction accuracy is improved, when clone metrics derived from the various clone detection tool are used.
AB - We have investigated through several experiments the differences in the fault-prone module prediction accuracy caused by the differences in the constituent code clone metrics of the prediction model. In the previous studies, they use one or more code clone metrics as independent variables to build an accurate prediction model. While they often use the clone detection method proposed by Kamiya et al. to calculate these metrics, the effect of the detection method on the prediction accuracy is not clear. In the experiment, we built prediction models using a dataset collected from an open source software project. The result suggests that the prediction accuracy is improved, when clone metrics derived from the various clone detection tool are used.
UR - http://www.scopus.com/inward/record.url?scp=84978042708&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84978042708&partnerID=8YFLogxK
U2 - 10.1109/SANER.2016.65
DO - 10.1109/SANER.2016.65
M3 - Conference contribution
AN - SCOPUS:84978042708
SP - 15
EP - 16
BT - 2016 IEEE 23rd International Conference on Software Analysis, Evolution, and Reengineering, SANER 2016
PB - Institute of Electrical and Electronics Engineers Inc.
ER -