Selection of Reliability Software Model Base on Deep Learning

  • Shiza Niazi Jehanzeb Niazi Lahore Garrison University
Keywords: Data minning, Deep learning

Abstract

Abstract
Previously, numerous product unwavering quality models have been proposed by some of analyst. Likewise, a few model choice criteria, for example, Akaike's information criterion, mean square flaws, anticipated relative mistake, etc, have been utilized for the determination of ideal programming dependability models (Date, 2019) [1]. Those appraisal criteria can be valuable for product administrators to survey the past pattern of flaw information. In any case, it is critical to survey the expectation exactness of model after the finish of short-coming information perception in the real programming venture. Right now paper, we propose a strategy for ideal programming unwavering quality model determination in light of the deep learning. Besides, we show a few numerical models of programming unwavering quality appraisal in the real programming ventures. Specifically, we talk about the expected programming cost and ideal discharge time in wording of models determination dependent on the deep learning.

References

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Published
2020-03-23
How to Cite
[1]
S. N. Jehanzeb Niazi, “Selection of Reliability Software Model Base on Deep Learning ”, IJCBS, vol. 1, no. 1, Mar. 2020.
Section
Articles