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Combining the requirement information for software defect estimation in design time |
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| Affiliation: | 1. AGH University of Science and Technology, Mickiewicza 30, Krakow 30-059, Poland;2. Birmingham City University, Faculty Computing, Engineering & the Built Environment, Millenium Point, Curzon Street, Birmingham B4 7XG, UK;3. University of Technology of Troyes, CNRS UMR 6281, Physics, Mechanics, Material and Nanotechnology Department ICD/LASMIS, 12 rue Marie Curie, 10004 Troyes Cedex, France |
| Abstract: | This paper analyzes the ability of requirement metrics for software defect prediction. Statistical significance tests are used to compare six machine learning algorithms on the requirement metrics, design metrics, and combination of both metrics in our analysis. The experimental results show the effectiveness of the predictor built on the combination of the requirement and design metrics in the early phase of the software development process. |
| Keywords: | Machine learning Software defect prediction Design metric Requirement metric Software engineering |
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