TY - JOUR
T1 - An Empirical Study of Fault Triggers in the Linux Operating System
T2 - An Evolutionary Perspective
AU - Xiao, Guanping
AU - Zheng, Zheng
AU - Yin, Beibei
AU - Trivedi, Kishor S.
AU - Du, Xiaoting
AU - Cai, Kai Yuan
N1 - Publisher Copyright:
© 1963-2012 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - This paper presents an empirical study of 5741 bug reports for the Linux kernel from an evolutionary perspective, with the aim of obtaining a deep understanding of bug characteristics in the Linux operating system. Bug classification is performed based on the fault triggering conditions, followed by an analysis of the proportions and evolution of the bug types as well as comparisons among versions, products, and repair locations. In addition, an analysis of regression bugs and the relationship between the types of bugs and the time needed to fix them are presented. Moreover, a procedure for the analysis of bug type characteristics based on complex network metrics is proposed, and four network metrics, i.e., degree, clustering coefficient, betweenness, and closeness, are utilized to further investigate the relationship between bug types and software metrics. In this paper, 22 interesting findings based on the empirical results are revealed, and guidance based on these findings is provided for developers and users.
AB - This paper presents an empirical study of 5741 bug reports for the Linux kernel from an evolutionary perspective, with the aim of obtaining a deep understanding of bug characteristics in the Linux operating system. Bug classification is performed based on the fault triggering conditions, followed by an analysis of the proportions and evolution of the bug types as well as comparisons among versions, products, and repair locations. In addition, an analysis of regression bugs and the relationship between the types of bugs and the time needed to fix them are presented. Moreover, a procedure for the analysis of bug type characteristics based on complex network metrics is proposed, and four network metrics, i.e., degree, clustering coefficient, betweenness, and closeness, are utilized to further investigate the relationship between bug types and software metrics. In this paper, 22 interesting findings based on the empirical results are revealed, and guidance based on these findings is provided for developers and users.
KW - Bug classification
KW - Linux operating system (OS)
KW - Mandelbug (MAN)
KW - complex network
KW - evolution
KW - fault trigger
KW - regression bug
UR - https://www.scopus.com/pages/publications/85076035095
U2 - 10.1109/TR.2019.2916204
DO - 10.1109/TR.2019.2916204
M3 - 文章
AN - SCOPUS:85076035095
SN - 0018-9529
VL - 68
SP - 1356
EP - 1383
JO - IEEE Transactions on Reliability
JF - IEEE Transactions on Reliability
IS - 4
M1 - 8731682
ER -