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ACCENTS Transactions on Information Security (TIS)

ISSN (Print):XXXX    ISSN (Online):2455-7196
Volume-5 Issue-17 January-2020
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Paper Title : Object oriented quality prediction through artificial intelligence and machine learning: a survey
Author Name : Jitendrea Kumar Saha, Kailash Patidar, Rishi Kushwah and Gaurav Saxena
Abstract :

Software quality estimation is an important aspect as it eliminates design and code defects. Object- oriented quality metrics prediction can help in the estimation of software quality of any defects and the chances of errors. In this paper a survey and the case analytics have been presented for the object-oriented quality prediction. It shows the analytical and experimental aspects of previous methodologies. This survey also elaborates different object-oriented parameters which is useful for the same problem. It also elaborates the problem aspects as well the limitations for the future directions. Machine learning and artificial intelligence methods have been considered mostly for this survey. The parameters considered are inheritance, dynamic behavior, encapsulation, objects etc.

Keywords : Software quality, Object-oriented metrics, Object-oriented parameters, Inheritance, Encapsulation.
Cite this article : Saha JK, Patidar K, Kushwah R, Saxena G. Object oriented quality prediction through artificial intelligence and machine learning: a survey. ACCENTS Transactions on Information Security. 2020; 5 (17): 1-5. DOI:10.19101/TIS.2020.517005.