一句话：提出使用有限状态模型对多个执行日志进行差分，以刻画不同运行集合之间的差异。
从运行系统日志中抽取模型已有大量研究，但在演化、测试或恶意软件分析等场景中，工程师通常需要比较来自不同运行集合的多个日志，而非仅分析单个日志；此时日志之间的差异才是关注目标。该论文提出使用有限状态模型进行日志差分，即通过为日志建立有限状态模型并比较模型来识别日志差异。给出的摘要仅阐述问题动机，未说明具体建模与差分算法、工具实现及实验评估，因此无法获知其精度、可扩展性或与既有方法的对比结果。该工作的核心价值在于将多日志差分问题置于有限状态模型比较框架下。
Much work has been published on extracting various kinds of models from logs that document the execution of running systems. In many cases, however, for example in the context of evolution, testing, or malware analysis, engineers are interested not only in a single log but in a set of several logs, each of which originated from a different set of runs of the system at hand. Then, the difference between the logs is the main target of interest.
DOI 原文 ·
@inproceedings{paperbot4627,
title = {Using finite-state models for log differencing},
author = {Hen Amar and Lingfeng Bao and Nimrod Busany and David Lo and Shahar Maoz},
booktitle = {FSE},
year = {2018},
doi = {10.1145/3236024.3236069}
}