Earticle

초록

영어

Launch Vehicle software has played an important role in Launch Vehicle system. However, the reliability assessment of Launch Vehicle software is still a hard problem due to the complexity of Launch Vehicle software. Failure prediction can be an effective approach of Launch Vehicle reliability evaluation, whereas failure prediction of software has not yet been fully explored. In this paper, a Markov Bayesian Network model for Launch Vehicle software failure prediction (MBNG) is proposed. In MBNG, unique features of Launch Vehicle software is considered as an important part in the modeling process, which improves the effectiveness of this novel model. Experiments are conducted to verify the effectiveness of MBNG model and compare its performance with classic models.

목차

Abstract
 1. Introduction
 2. Bayesian Network Model
 3. Modeling and Deduction
  3.1. Determine the Distributions
  3.2. Software Failure Prediction when Parameters in Distributions are Known
 4. Case study
  4.1. Subject Programs
  4.2. Experimental Results
  4.3. Threats to Validity
 5. Discussion
 References

키워드

저자

• Tinggui Yan [ College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China ]
• Xiaoqian Chen [ College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China ]
• Shipeng Li [ Beijing Institute of Astronautical System Engineering, China Academy of Launch Vehicle Technology, Beijing, China ]
• Li Ma [ Beijing Institute of Astronautical System Engineering, China Academy of Launch Vehicle Technology, Beijing, China ]
• Jian Bai [ Beijing Institute of Astronautical System Engineering, China Academy of Launch Vehicle Technology, Beijing, China ]
• Zhifang Yang [ Beijing Institute of Astronautical System Engineering, China Academy of Launch Vehicle Technology, Beijing, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605