Characterizing the Natural Language Descriptions in Software Logging Statements

Pinjia He, Zhuangbin Chen, Shilin He, Michael R. Lyu
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引用次数: 77

Abstract

Logging 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.
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软件日志语句中自然语言描述的特征
日志记录是现代软件开发中非常重要的一种常见编程实践,因为软件日志已广泛用于各种软件维护任务。为了提供高质量的日志,开发人员需要仔细设计日志语句中的描述文本。不恰当的描述将减慢甚至误导维护过程,例如事后分析。然而,目前对于开发者日志行为缺乏严格的指导和规范,这使得日志语句中描述文本的构建成为一个具有挑战性的问题。为了填补这一重要的空白,在本文中,我们系统地研究了开发人员记录的内容,重点是在日志记录语句中使用自然语言描述。通过对10个Java项目和7个c#项目进行源代码分析,我们获得了6个有价值的发现,这些项目总共包含28,532,975条LOC和115,159条日志语句。此外,我们的研究通过使用简单的信息检索方法获得高达49.04的BLEU-4分数和62.1的ROUGE-L分数,证明了日志语句自动描述文本生成的潜力。为了促进这一领域未来的研究,这些数据集已经公开发布。
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