一句话：提出利用软件缺陷知识图谱整合多源缺陷知识，以提升缺陷理解与修复效率。
软件演化过程中缺陷不断出现，随着软件规模与复杂度增长，缺陷修复愈发困难。开源项目的缺陷与提交数据、问答文档等软件资源中蕴含大量缺陷知识，可帮助开发者理解和修复缺陷。然而，现有工作多从单一软件资源中孤立地挖掘数据来辅助修复，可能降低修复效率。本文提出基于软件缺陷知识图谱的智能缺陷修复思路，旨在通过知识图谱整合多源缺陷知识，为缺陷修复提供更全面的知识支持。摘要未给出具体实现细节与实验评估结果。
Software bugs continuously emerge during the process of software evolution. With the increasing size and complexity of software, bug fixing becomes increasingly more difficult. Bug and commit data of open source projects, Q&A documents and other software resources contain a sea of bug knowledge which can be utilized to help developers understand and fix bugs. Existing work focuses on data mining from a certain software resource in isolation to assist in bug fixing, which may reduce the efficiency of bug fixing.
DOI 原文 ·
@inproceedings{paperbot4655,
title = {Intelligent bug fixing with software bug knowledge graph},
author = {Cheng Zhou},
booktitle = {FSE},
year = {2018},
doi = {10.1145/3236024.3275428}
}