DocumentCode
659279
Title
A reliability prediction model for complex systems using data flow dependency
Author
Majumdar, Deyasini ; Mallick, Shankhanaad
Author_Institution
RCC Inst. of Inf. Technol., Kolkata, India
fYear
2013
fDate
13-14 Sept. 2013
Firstpage
144
Lastpage
148
Abstract
Research on software reliability prediction is of great practical importance. Failure characteristic of large and complex software depends on the operations of individual components and their architecture. Complexity of the components as well as their dependency provides a greater impact on overall reliability of the software. Reliability prediction in the early stage of component based software requires the knowledge of interconnection between the components as well as propagation of errors between the components. In this paper we propose a reliability prediction model which not only considers the control flow of the component it also considers data sharing between the components and their deployment details. We propose a new graphical structure Data Flow Dependency Graph to estimate the effective reliability of the data processed by the components and then use the operational profile to predict the reliability.
Keywords
data flow graphs; data structures; object-oriented programming; software architecture; software fault tolerance; system recovery; complex systems; component based software; component complexity; component control flow; data flow dependency graph; data sharing; error propagation; failure characteristic; graphical structure; interconnection knowledge; software architecture; software reliability prediction model; Data models; Predictive models; Software architecture; Software reliability; Software systems; Software reliability; based software; software architecture;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Trends and Applications in Computer Science (ICETACS), 2013 1st International Conference on
Conference_Location
Shillong
Print_ISBN
978-1-4673-5249-9
Type
conf
DOI
10.1109/ICETACS.2013.6691412
Filename
6691412
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