图 书 馆
挖掘边缘加权的调用图本地化软件错误Mining Edge-Weighted Call Graphs to Localise Software Bugs |
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| 课程网址: | http://videolectures.net/ecmlpkdd08_eichinger_mewc/ |
| 主讲教师: | Frank Eichinger, Klemens Böhm, Matthias Huber |
| 开课单位: | 卡尔斯鲁厄理工学院 |
| 开课时间: | 2008-10-10 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | An important problem in software engineering is the automated discovery of noncrashing occasional bugs. In this work we address this problem and show that mining of weighted call graphs of program executions is a promising technique. We mine weighted graphs with a combination of structural and numerical techniques. More specifically, we propose a novel reduction technique for call graphs which introduces edge weights. Then we present an analysis technique for such weighted call graphs based on graph mining and on traditional feature selection schemes. The technique generalises previous graph mining approaches as it allows for an analysis of weights. Our evaluation shows that our approach finds bugs which previous approaches cannot detect so far. Our technique also doubles the precision of finding bugs which existing techniques can already localise in principle. |
| 关 键 词: | 错误自动发现; 加权调用图挖掘; 权重分析 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-11：dingaq |
| 阅读次数: | 40 |