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| Content Provider | ACM Digital Library |
|---|---|
| Author | Lin, Qingwei Zhu, Jieming Lou, Jian-Guang Xie, Tao Hu, Wenlu Ding, Rui Zhang, Dongmei Fu, Qiang |
| Abstract | System logs are widely used in various tasks of software system management. It is crucial to avoid logging too little or too much. To achieve so, developers need to make informed decisions on where to log and what to log in their logging practices during development. However, there exists no work on studying such logging practices in industry or helping developers make informed decisions. To fill this significant gap, in this paper, we systematically study the logging practices of developers in industry, with focus on where developers log. We obtain six valuable findings by conducting source code analysis on two large industrial systems (2.5M and 10.4M LOC, respectively) at Microsoft. We further validate these findings via a questionnaire survey with 54 experienced developers in Microsoft. In addition, our study demonstrates the high accuracy of up to 90% F-Score in predicting where to log. . |
| Starting Page | 24 |
| Ending Page | 33 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450327688 |
| DOI | 10.1145/2591062.2591175 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-05-31 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Automatic logging Logging practice Developer survey |
| Content Type | Text |
| Resource Type | Article |
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