Authors:
Wenjing Liu
1
;
2
;
Zhiwei Xu
3
;
Limin Liu
1
and
Yunzhan Gong
2
Affiliations:
1
College of Data Science and Application, Inner Mongolia University of Technology, Hohhot 100080, China
;
2
State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
;
3
Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
Keyword(s):
Large-Scale Software, Incremental Reliability Assessment, Structure Sequentialization, Theoretical Reduction, Importance Sampling Based Reliability Assessment.
Abstract:
Problems of software quality assurance and behavior prediction of large-scale software systems have high importance due to the fact that software systems are getting more prevalent in almost all areas of human activities, and always include an large number of modules. To continuously offer significant changes or major improvements over the existing system, software upgrading is inevitable. This involves additional difficulty to assess reliability and guarantee the quality assurance of the large-scale system. The existing reliability assessment methods cannot continuously yet effectively assess the software reliability because the program structure of the software is not taken into account to drive the assessment process. Thus, it is highly desired to estimate the software reliability in an incremental way. This paper incorporates theoretical sequentialization and reduction of the program structure into sampling-based software reliability evaluation. Specifically, we leverage importan
ce sampling to evaluate reliability rates of sequence structures, branch structures and loop structures in the software, as well as transition probabilities among these structures. In addition, we sequentialize program structures to support the aggregation of reliability assessment results corresponding to different structures. Finally, a real-world case study is provided as a practical application of the proposed incremental assessment model.
(More)