图 书 馆
跟踪概念的变化与增量提高的不断变化的指数损失Tracking Concept Change with Incremental Boosting by Minimization of the Evolving Exponential Loss |
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| 课程网址: | http://videolectures.net/ecmlpkdd2011_grbovic_loss/ |
| 主讲教师: | Mihajlo Grbovic |
| 开课单位: | 天普大学 |
| 开课时间: | 信息不详。欢迎您在右侧留言补充。 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Fault localization, i.e., identifying erroneous lines of code in a buggy program, is a tedious process, which often requires considerable manual effort and is costly. Recent years have seen much progress in techniques for automated fault localization, specifically using program spectra - executions of failed and passed test runs provide a basis for isolating the faults. Despite the progress, fault localization in large programs remains a challenging problem, because even inspecting a small fraction of the lines of code in a large problem can require substantial manual effort. This paper presents a novel framework for fault localization based on latent divergences - an effective method for feature selection in machine learning. Our insight is that the problem of fault localization can be reduced to the problem of feature selection, where lines of code correspond to features. We also present an experimental evaluation of our framework using the Siemens suite of subject programs, which are a standard benchmark for studying fault localization techniques in software engineering. The results show that our framework enables more accurate fault localization than existing techniques. |
| 关 键 词: | 计算机科学; 机器学习; 助推 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-12-05：cwx |
| 阅读次数: | 34 |