Characterizing the Natural Language Descriptions in Software Logging Statements
Refereed conference paper presented and published in conference proceedings


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AbstractLogging is a common programming practice of great importance in modern software development, because software logs have been widely used in various software maintenance tasks. To provide high-quality logs, developers need to design the description text in logging statements carefully. Inappropriate descriptions will slow down or even mislead the maintenance process, such as postmortem analysis. However, there is currently a lack of rigorous guide and specifications on developer logging behaviors, which makes the construction of description text in logging statements a challenging problem. To fill this significant gap, in this paper, we systematically study what developers log, with focus on the usage of natural language descriptions in logging statements. We obtain 6 valuable findings by conducting source code analysis on 10 Java projects and 7 C# projects, which contain 28,532,975 LOC and 115,159 logging statements in total. Furthermore, our study demonstrates the potential of automated description text generation for logging statements by obtaining up to 49.04 BLEU-4 score and 62.1 ROUGE-L score using a simple information retrieval method. To facilitate future research in this field, the datasets have been publicly released.
All Author(s) ListPinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu
Name of Conference33rd IEEE/ACM International Conference on Automated Software Engineering, ASE 2018
Start Date of Conference03/09/2018
End Date of Conference07/09/2018
Place of ConferenceMontpellier, France
Country/Region of ConferenceFrance
Proceedings TitleASE 2018, Proceedings of the 33rd ACM/IEEE International Conference on Automated Software Engineering
Year2018
Month9
PublisherACM/IEEE
Pages178 - 189
ISBN978-145035937-5
LanguagesEnglish-United States

Last updated on 2021-08-05 at 00:38