TY - GEN
T1 - Analysis of the Influence of Total Number of Software Faults on SRGM Performance
AU - Sun, Zhichao
AU - Zhang, Ce
AU - Yuan, Yu Fei
AU - Jiang, Wenqian
AU - Fan, Miaomiao
AU - Li, Wenyu
AU - Wen, Yafei
AU - Song, Wen
AU - Liu, Kaiwei
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/5/21
Y1 - 2021/5/21
N2 - The total number of software failures is an important parameter in the software reliability growth model SRGM (Software Reliability Growth Model), which plays an important role in guiding software reliability estimation, software testing management and software release strategies. In this paper, the five types of software failure total models are summarized and analyzed, and four total failure functions under imperfect troubleshooting are selected: the optimistic type with limited growth (exponential growth), and the pessimistic type with unlimited growth (linear growth and linear growth). Exponential growth) and compromise types, and conducted experiments on 9 public real failure data sets to explore the impact of the software total failure model on the fitting performance and prediction performance of SRGM. The results show that the fitting and prediction performance of the software total failure a(t) function to SRGM depends on the consistency of the a(t) model based on subjective assumptions and the objective real failure data set. Finally, it summarizes the full text and points out the future research direction of total software failure.
AB - The total number of software failures is an important parameter in the software reliability growth model SRGM (Software Reliability Growth Model), which plays an important role in guiding software reliability estimation, software testing management and software release strategies. In this paper, the five types of software failure total models are summarized and analyzed, and four total failure functions under imperfect troubleshooting are selected: the optimistic type with limited growth (exponential growth), and the pessimistic type with unlimited growth (linear growth and linear growth). Exponential growth) and compromise types, and conducted experiments on 9 public real failure data sets to explore the impact of the software total failure model on the fitting performance and prediction performance of SRGM. The results show that the fitting and prediction performance of the software total failure a(t) function to SRGM depends on the consistency of the a(t) model based on subjective assumptions and the objective real failure data set. Finally, it summarizes the full text and points out the future research direction of total software failure.
UR - https://www.scopus.com/pages/publications/85122618808
U2 - 10.1145/3474198.3478160
DO - 10.1145/3474198.3478160
M3 - 会议稿件
AN - SCOPUS:85122618808
T3 - ACM International Conference Proceeding Series
BT - ICFEICT 2021 - International Conference on Frontiers of Electronics, Information and Computation Technologies, Conference Proceedings
PB - Association for Computing Machinery
T2 - 2021 International Conference on Frontiers of Electronics, Information and Computation Technologies, ICFEICT 2021
Y2 - 21 May 2021 through 23 May 2021
ER -