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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Parizy, M. Takayama, K. Kanazawa, Y. |
| Copyright Year | 2014 |
| Description | Author affiliation: Design Eng. Lab., FUJITSU Labs. Ltd., Kawasaki, Japan (Parizy, M.; Takayama, K.; Kanazawa, Y.) |
| Abstract | While mining software repositories is a field which has greatly grown over the last ten years, Large Scale Integrated circuit (LSI) design repository mining has yet to reach the momentum of software's. We felt that it represents untouched potential especially for defect prediction. In an LSI, referred to as hardware later on, verification has a high cost compared to design. After studying existing software defect prediction techniques based on repository mining, we decided to adapt some for hardware design repositories in the hope of saving precious resources by focusing design and verification effort on the most defect prone parts of the design. By focusing our resources on the previously mentioned parts, we hope to improve our designs quality. We discuss how we applied these prediction techniques to hardware and show our results are promising for the future of hardware repository mining. Our results allowed us to estimate a possible total verification time reduction of 12%. |
| Starting Page | 565 |
| Ending Page | 568 |
| File Size | 570457 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781479961467 |
| ISSN | 10636773 |
| DOI | 10.1109/ICSME.2014.96 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2014-09-29 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Hardware Software Data mining Entropy Measurement Hardware design languages Correlation code metrics defect prediction hardware LSI repository mining code change |
| Content Type | Text |
| Resource Type | Article |
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