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| O. Mizuno, N. Kawashima, and K. Kawamoto, "Fault-Prone Module Prediction Approaches Using Identifiers in Source Code," ACIS International Journal of Software Innovation, 3(1), pp. 36-49, January 2015. | |
| ID | 691 |
| 分類 | 学術論文誌(査読付) |
| タグ | approaches code fault-prone identifiers module prediction source |
| 表題 (title) |
Fault-Prone Module Prediction Approaches Using Identifiers in Source Code |
| 表題 (英文) |
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| 著者名 (author) |
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto |
| 英文著者名 (author) |
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto |
| キー (key) |
Osamu Mizuno,Naoki Kawashima,Kimiaki Kawamoto |
| 定期刊行物名 (journal) |
ACIS International Journal of Software Innovation |
| 定期刊行物名 (英文) |
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| 巻数 (volume) |
3 |
| 号数 (number) |
1 |
| ページ範囲 (pages) |
36-49 |
| 刊行月 (month) |
1 |
| 出版年 (year) |
2015 |
| Impact Factor (JCR) |
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| URL |
DOI: 10.4018/ijsi.2015010103 |
| 付加情報 (note) |
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| 注釈 (annote) |
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| 内容梗概 (abstract) |
Prediction of fault-prone modules is an important area of software engineering. The authors assumed that the occurrence of faults is related to the semantics in the source code modules. Semantics in a software module can be extracted from identifiers in the module. Identifiers such as variable names and function names in source code are thus essential information to understand code. The naming for identifiers affects on code understandability; thus, the authors expect that they affect software quality. In this study, the authors examine the relationship between the length of identifiers and existence of software faults in a software module. Furthermore, the authors analyze the relationship between occurrence of “words” in identifiers and the existence of faults. From the experiments using the data from open source software, the authors modeled the relationship between the fault occurrence and the length of identifiers, and the relationship between the fault occurrence and the word in identifiers by the random forest technique. The result of the experiment showed that the length of identifiers can predict the fault-proneness of the software modules. Also, the result showed that the word occurrence model is as good a measure as traditional CK and LOC metrics models.
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| 論文電子ファイル | 利用できません． |
| BiBTeXエントリ |
@article{id691,
title = {Fault-prone Module Prediction Approaches Using Identifiers in Source Code},
author = {Osamu Mizuno and Naoki Kawashima and Kimiaki Kawamoto},
journal = {ACIS International Journal of Software Innovation},
volume = {3},
number = {1},
pages = {36-49},
month = {1},
year = {2015},
}
|