一句话：提出 NAR-miner，从源代码挖掘 A⇒¬B 形式的负关联规则，以检测违反互斥或冲突关系引发的缺陷。
从源代码中挖掘编程规则并据此检测缺陷已被证明有效，但现有研究主要关注 A⇒B 形式的正向规则，即操作 A 出现时操作 B 也应出现。对于 A⇒¬B 形式的负向规则，即程序元素之间的互斥或冲突关系，现有工作尚未给予足够重视。本文提出 NAR-miner，从代码中发现否定关联规则，并用于缺陷检测。作者指出，违反此类负向规则同样会导致严重 bug，因此挖掘并利用负关联规则具有重要价值。摘要未给出具体数据集与实验结果。
Inferring programming rules from source code based on data mining techniques has been proven to be effective to detect software bugs. Existing studies focus on discovering positive rules in the form of A ⇒ B, indicating that when operation A appears, operation B should also be here. Unfortunately, the negative rules (A ⇒ ¬ B), indicating the mutual suppression or conflict relationships among program elements, have not gotten the attention they deserve. In fact, violating such negative rules can also result in serious bugs.
DOI 原文 ·
@inproceedings{paperbot4666,
title = {NAR-miner: discovering negative association rules from code for bug detection},
author = {Pan Bian and Bin Liang and Wenchang Shi and Jianjun Huang and Yan Cai},
booktitle = {FSE},
year = {2018},
doi = {10.1145/3236024.3236032}
}