###
计算机系统应用英文版:2023,32(3):217-223
本文二维码信息
码上扫一扫!
不正确程序修复补丁识别
(中国石油大学(华东) 计算机科学与技术学院, 青岛 266580)
Identification of Incorrect Program Repair Patches
(College of Computer Science and Technology, China University of Petroleum, Qingdao 266580, China)
摘要
图/表
参考文献
相似文献
本文已被:浏览 578次   下载 1287
Received:July 26, 2022    Revised:August 26, 2022
中文摘要: 程序自动修复技术是保证软件质量、提高开发效率的有效手段. 目前, 大多数自动修复工具使用测试用例作为补丁正确性验证的最终方法, 有限的测试用例难以对程序进行充分的测试, 因此自动修复工具生成的补丁集合包含大量的不正确补丁. 为了识别不正确补丁, 我们采用对比缺陷修复前后成功测试的执行路径以及生成测试用例的方法来识别修复补丁的有效性, 以解决自动修复工具精度低的问题. 我们的方法评估了来自6个经典的自动修复工具生成的132个补丁, 并成功地排除了80个不正确的补丁并且没有排除正确的补丁, 这表明我们的方法可以有效地排除不正确补丁, 并且提高自动修复工具的精度.
Abstract:Automatic program repair is an effective technology for ensuring software quality and improving development efficiency. At present, most automatic repair tools use test cases as the final method of patch correctness verification. However, program can barely be fully tested by limited test cases. Consequently, patch sets generated by automatic repair tools contain a large number of incorrect patches. To identify such patches, this study identifies the effectiveness of repair patches by comparing the execution paths of successful tests before and after defect repair and the methods of test case generation to solve the low accuracy problem of automatic repair tools. When the proposed method is applied to evaluate 132 patches generated by six classic repair tools, it successfully excludes 80 incorrect patches, without excluding correct ones. This result shows that the proposed method can effectively exclude incorrect patches and improve the accuracy of automatic repair tools.
文章编号:     中图分类号:    文献标志码:
基金项目:山东省自然科学基金(ZR2021MF058)
引用文本:
董玉坤,唐道龙,孙玉雪,位欣欣.不正确程序修复补丁识别.计算机系统应用,2023,32(3):217-223
DONG Yu-Kun,TANG Dao-Long,SUN Yu-Xue,WEI Xin-Xin.Identification of Incorrect Program Repair Patches.COMPUTER SYSTEMS APPLICATIONS,2023,32(3):217-223