Assessments of Computational Intelligence Techniques for Predicting Reliability of Componentbased Software Parameter and Design Issues
In this growing era of complex computation and robotics, software reliability is a major concern for software developers. The development of high-quality software, with cost, time, and customer satisfaction as driving forces, reuse of modules/components are on the rise. In a component-based approach, the software can be developed from the existing component, primarily through incorporating and substituting individual components/modules. Hence, one component may be reused in various applications, providing a speedy evolution and enhancement of applications with high quality and reduced cost. While choosing and integrating different components we should focus on different parameters for achieving reliable software using computational intelligence techniques. Computational intelligence techniques help in predicting the faults in real-time with increased accuracy, resulting in software that is less prone to errors. The objective of the paper is to present various quality aspects of Component-Based Systems (CBS) and to determine the relationship between CBS quality parameters for assessment of component intelligence technique. We have presented various design issues that came across while developing the reliability model, and also mentioned different parameters affecting software reliability. Literature review of computational intelligence techniques has been done and their functionalities, benefits, limitations, etc., highlighted
Year of publication: |
2020
|
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Authors: | Yadav, Shivani |
Other Persons: | Kishan, Bal (contributor) |
Publisher: |
[2020]: [S.l.] : SSRN |
Subject: | Prognoseverfahren | Forecasting model | Software | Künstliche Intelligenz | Artificial intelligence | Neuronale Netze | Neural networks |
Saved in:
freely available
Extent: | 1 Online-Ressource (20 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | In: International Journal of Advanced Research in Engineering and Technology, 11(6), 2020, pp. 565-584 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments July 21, 2020 erstellt |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012827769
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