scholarly journals Refining reliability estimation of mobile software systems

Author(s):  
Roshanak Roshandel ◽  
Sam Malek
2004 ◽  
Vol 29 (1) ◽  
pp. 243-248
Author(s):  
Paola Bracchi ◽  
Vittorio Cortellessa

Author(s):  
Yaguang Yang

System safety is closely related to system reliability. Safety requirements many times are translated to reliability requirements. Nowadays, software systems exist in many engineering systems. However, there is no consensus method for software reliability estimation. On the contrary, there is an increasing interest in estimating the software reliability due to concerns for safety-critical systems. In this article, we try to close the gap by proposing a systematic and probabilistic method to estimate the software reliability based on software test data.


Author(s):  
Preeti Malik ◽  
Lata Nautiyal ◽  
Mangey Ram

Component-based software engineering has proved itself as a strong pillar in software engineering community. Large number of factors are involved in the success of software product developed using Component-based software engineering, for instance, security, reliability, quality, safety, and testability. As the component-based software is made up of large number of components put together, therefore components’ reliability influence the reliability of the complete software. Numerous models and principles have been established to estimate the reliability of software by applying information regarding architecture, quality and security attributes of the software. Many researchers overlooked a major factor while estimating reliability of component-based software and that is error-propagation. Although it can be a case that the components are not dependent on each other and they are supplemented with the wrappers. However it is not true for many component-based applications. In this paper, a framework for reliability estimation has been proposed. In our proposal we have considered error propagation. We have analyzed the program structure and also presented how they are handled in estimation process. Further sensitivity analysis is done to identify the most sensitive component of the system. A numerical simulation is also presented for better understanding of the proposed framework.


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