Name
Abstract | ||
|---|---|---|
Many change classification techniques have been proposed to identify defect-prone changes. These techniques consider all developers' historical change data to build a global prediction model. In practice, since developers have their own coding preferences and behavioral patterns, which causes different defect patterns, a separate change classification model for each developer can help to improve p... |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TR.2016.2588139 | IEEE Transactions on Reliability |
Keywords | Field | DocType |
Data models,Predictive models,Software,Computer bugs,Genetic algorithms,Feature extraction,Buildings | Data mining,Data modeling,Computer science,Software bug,Coding (social sciences),Feature extraction,Software,Reliability engineering,Genetic algorithm,Source lines of code,Linux kernel | Journal |
Volume | Issue | ISSN |
65 | 4 | 0018-9529 |
Citations | PageRank | References |
10 | 0.42 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xin Xia | 1 | 972 | 65.97 |
| David Lo | 2 | 5346 | 259.67 |
| xinyu | 3 | 590 | 30.19 |
| Xiaohu Yang | 4 | 125 | 8.71 |