一句话：提出 TeLL，对多层级代码块信息建模，综合利用块内与块间特征为日志语句推荐合适的详细级别。
日志语句是软件调试与维护的重要基础，每条日志通常被赋予一个详细级别（如 trace、error）。然而，由于缺乏关于日志级别使用规范的明确说明，开发者选择恰当级别时既困难又容易出错。已有方案主要依据日志语句所在代码块内部的特征（intra-block features）来推荐级别，却忽略了周边代码块所提供的信息（inter-block features），而这些信息同样对刻画日志特征至关重要。本文提出 TeLL，通过对多层级代码块信息进行建模，融合块内与块间特征来完成日志级别建议。摘要未报告具体的实现细节与实验结果。
Developers insert logging statements into source code to monitor system execution, which forms the basis for software debugging and maintenance. For distinguishing diverse runtime information, each software log is assigned with a separate verbosity level (e.g., trace and error). However, choosing an appropriate verbosity level is a challenging and error-prone task due to the lack of specifications for log level usages. Prior solutions aim to suggest log levels based on the code block in which a logging statement resides (i.e., intra-block features). Such suggestions, however, do not consider information from surrounding blocks (i.e., inter-block features), which also plays an important role in revealing logging characteristics.
@inproceedings{paperbot7395,
title = {TeLL: log level suggestions via modeling multi-level code block information},
author = {Jiahao Liu and Jun Zeng and Xiang Wang and Kaihang Ji and Zhenkai Liang},
booktitle = {ISSTA},
year = {2022},
doi = {10.1145/3533767.3534379}
}