Predicting defective modules in different test phases
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| 024 | 7 | 0 | |a 10.1007/s11219-014-9230-x |2 doi |
| 035 | |a (NATIONALLICENCE)springer-10.1007/s11219-014-9230-x | ||
| 245 | 0 | 0 | |a Predicting defective modules in different test phases |h [Elektronische Daten] |c [Bora Caglayan, Ayse Tosun Misirli, Ayse Bener, Andriy Miranskyy] |
| 520 | 3 | |a Defect prediction is a well-established research area in software engineering . Prediction models in the literature do not predict defect-prone modules in different test phases. We investigate the relationships between defects and test phases in order to build defect prediction models for different test phases. We mined the version history of a large-scale enterprise software product to extract churn and static code metrics. We used three testing phases that have been employed by our industry partner, namely function, system and field, to build a learning-based model for each testing phase. We examined the relation of different defect symptoms with the testing phases. We compared the performance of our proposed model with a benchmark model that has been constructed for the entire test phase (benchmark model). Our results show that building a model to predict defect-prone modules for each test phase significantly improves defect prediction performance and shortens defect detection time. The benefit analysis shows that using the proposed model, the defects are detected on the average 7months earlier than the actual. The outcome of prediction models should lead to an action in a software development organization. Our proposed model gives a more granular outcome in terms of predicting defect-prone modules in each testing phase so that managers may better organize the testing teams and effort. | |
| 540 | |a Springer Science+Business Media New York, 2014 | ||
| 690 | 7 | |a Software testing |2 nationallicence | |
| 690 | 7 | |a Testing phase |2 nationallicence | |
| 690 | 7 | |a Defect prediction |2 nationallicence | |
| 700 | 1 | |a Caglayan |D Bora |u Department of Computer Engineering, Bogazici University, P.K. 2 TR-34342, Bebek, Istanbul, Turkey |4 aut | |
| 700 | 1 | |a Tosun Misirli |D Ayse |u Department of Information Processing Science, Oulu University, Oulu, Finland |4 aut | |
| 700 | 1 | |a Bener |D Ayse |u Data Science Lab, Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, M5B 2K3, Toronto, ON, Canada |4 aut | |
| 700 | 1 | |a Miranskyy |D Andriy |u Department of Computer Science, Ryerson University, 350 Victoria Street, M5B 2K3, Toronto, ON, Canada |4 aut | |
| 773 | 0 | |t Software Quality Journal |d Springer US; http://www.springer-ny.com |g 23/2(2015-06-01), 205-227 |x 0963-9314 |q 23:2<205 |1 2015 |2 23 |o 11219 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/s11219-014-9230-x |q text/html |z Onlinezugriff via DOI |
| 898 | |a BK010053 |b XK010053 |c XK010000 | ||
| 900 | 7 | |a Metadata rights reserved |b Springer special CC-BY-NC licence |2 nationallicence | |
| 908 | |D 1 |a research-article |2 jats | ||
| 949 | |B NATIONALLICENCE |F NATIONALLICENCE |b NL-springer | ||
| 950 | |B NATIONALLICENCE |P 856 |E 40 |u https://doi.org/10.1007/s11219-014-9230-x |q text/html |z Onlinezugriff via DOI | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Caglayan |D Bora |u Department of Computer Engineering, Bogazici University, P.K. 2 TR-34342, Bebek, Istanbul, Turkey |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Tosun Misirli |D Ayse |u Department of Information Processing Science, Oulu University, Oulu, Finland |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Bener |D Ayse |u Data Science Lab, Department of Mechanical and Industrial Engineering, Ryerson University, 350 Victoria Street, M5B 2K3, Toronto, ON, Canada |4 aut | ||
| 950 | |B NATIONALLICENCE |P 700 |E 1- |a Miranskyy |D Andriy |u Department of Computer Science, Ryerson University, 350 Victoria Street, M5B 2K3, Toronto, ON, Canada |4 aut | ||
| 950 | |B NATIONALLICENCE |P 773 |E 0- |t Software Quality Journal |d Springer US; http://www.springer-ny.com |g 23/2(2015-06-01), 205-227 |x 0963-9314 |q 23:2<205 |1 2015 |2 23 |o 11219 | ||