An Empirical Study of Regression Bug Chains in Linux

被引:9
|
作者
Xiao, Guanping [1 ]
Zheng, Zheng [1 ]
Jiang, Bo [2 ]
Sui, Yulei [3 ,4 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Comp Sci & Engn, Beijing 100191, Peoples R China
[3] Univ Technol Sydney, Ctr Artificial Intelligence, Sydney, NSW 2007, Australia
[4] Univ Technol Sydney, Sch Software, Sydney, NSW 2007, Australia
基金
中国国家自然科学基金; 澳大利亚研究理事会;
关键词
Bipartite network; bug-fixing commit (BFC); bug-introducing commit (BIC); Linux; regression bug; regression bug chain (RBC);
D O I
10.1109/TR.2019.2902171
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Regression bugs are a type of bugs that cause a feature of software that worked correctly but stop working after a certain software commit. This paper presents a systematic study of regression bug chains, an important but unexplored phenomenon of regression bugs. Our paper is based on the observation that a commit c1, which fixes a regression bug b1, may accidentally introduce another regression bug b2. Likewise, commit c2 repairing b2 may cause another regression bug b3, resulting in a bug chain, i.e., b1 -> c1 -> b2 -> c2 -> b3. We have conducted a large-scale study by collecting 1579 regression bugs and 2630 commits from 57 Linux versions (from 2.6.12 to 4.9). The relationships between regression bugs and commits are modeled as a directed bipartite network. Our major contributions and findings are fourfold: 1) a novel concept of regression bug chains and their formulation; 2) compared to an isolated regression bug, a bug on a regression bug chain is muchmore difficult to repair, costing 2.4xmore fixing time, involving 1.3x more developers and 2.8x more comments; 3) 85.8% of bugs on the chains in Linux reside in Drivers, ACPI, Platform Specific/Hardware, and Power Management; and 4) 83% of the chains affect only a single Linux subsystem, while 68% of the chains propagate across Linux versions.
引用
收藏
页码:558 / 570
页数:13
相关论文
共 50 条
  • [21] An empirical study on bug propagation through code cloning
    Mondal, Manishankar
    Roy, Banani
    Roy, Chanchal K.
    Schneider, Kevin A.
    JOURNAL OF SYSTEMS AND SOFTWARE, 2019, 158
  • [22] Fuzzing the Latest NTFS in Linux with Papora: An Empirical Study
    Lo, Edward
    He, Ningyu
    Shi, Yuejie
    Xu, Jiajia
    Wu, Chiachih
    Li, Ding
    Guo, Yao
    2023 IEEE SECURITY AND PRIVACY WORKSHOPS, SPW, 2023, : 326 - 336
  • [23] An Empirical Study of Security Problem Reports in Linux Distributions
    Anbalagan, Prasanth
    Vouk, Mladen
    ESEM: 2009 3RD INTERNATIONAL SYMPOSIUM ON EMPIRICAL SOFTWARE ENGINEERING AND MEASUREMENT, 2009, : 482 - 485
  • [24] Evaluating SZZ Implementations: An Empirical Study on the Linux Kernel
    Lyu, Yunbo
    Kang, Hong Jin
    Widyasari, Ratnadira
    Lawall, Julia
    Lo, David
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2024, 50 (09) : 2219 - 2239
  • [25] Adapting Linux for Mobile Platforms: An Empirical Study of Android
    Khomh, Foutse
    Yuan, Hao
    Zou, Ying
    2012 28TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE MAINTENANCE (ICSM), 2012, : 629 - 632
  • [26] Instant Bug Testing Service for Linux Kernel
    Chen, Yu
    Wu, Fengguang
    Yu, Kuanlong
    Zhang, Lei
    Chen, Yuheng
    Yang, Yang
    Mao, Junjie
    2013 IEEE 15TH INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING AND COMMUNICATIONS & 2013 IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (HPCC_EUC), 2013, : 1860 - 1865
  • [27] Linux Bug Represents Major Internet Threat
    不详
    COMPUTER, 2015, 48 (03) : 18 - 18
  • [28] Using bug report as a software quality measure: An empirical study
    Yu, L. (ligyu@iusb.edu), 1600, Inderscience Enterprises Ltd., 29, route de Pre-Bois, Case Postale 856, CH-1215 Geneva 15, CH-1215, Switzerland (03):
  • [29] An Empirical Study of Bug Isolation on the Effectiveness of Multiple Fault Localization
    Li, Zheng
    Wu, Yonghao
    Liu, Yong
    2019 IEEE 19TH INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY (QRS 2019), 2019, : 18 - 25
  • [30] A comprehensive empirical study on bug characteristics of deep learning frameworks
    Yang, Yilin
    He, Tianxing
    Xia, Zhilong
    Feng, Yang
    INFORMATION AND SOFTWARE TECHNOLOGY, 2022, 151