scholarly journals A Comparative analysis of usage of Inheritance Metrics on software fault prediction using Machine Learning Technique

2020 ◽  
Vol 9 (3) ◽  
pp. 2794-2800
Author(s):  
Brihathi A
Keyword(s):  
Machine Learning ◽  
Comparative Analysis ◽  
Fault Prediction ◽  
Machine Learning Technique ◽  
Software Fault Prediction ◽  
Learning Technique ◽  
Software Fault

Machine learning based methods for software fault prediction: A survey

2021 ◽  
Vol 172 ◽  
pp. 114595
Author(s):  
Sushant Kumar Pandey ◽  
Ravi Bhushan Mishra ◽  
Anil Kumar Tripathi
Keyword(s):  
Machine Learning ◽  
Fault Prediction ◽  
Software Fault Prediction ◽  
Software Fault

scholarly journals Genetic Evolutionary Learning Fitness Function (GELFF) for Feature Diagnosis to Software Fault Prediction

2019 ◽  
Vol 8 (11S) ◽  
pp. 1151-1161
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Fitness Function ◽  
Fault Prediction ◽  
Evolutionary Learning ◽  
Software Fault Prediction ◽  
Underlying Process ◽  
Learning Function ◽  
Wide Range ◽  
Software Fault

Nowadays, proper feature selection f+orFault prediction is very perplexing task. Improper feature selection may lead to bad result. To avoid this, there is a need to find the aridity of software fault. This is achieved by finding the fitness of the evolutionaryAlgorithmic function. In this paper, we finalize the Genetic evolutionarynature of our Feature set with the help of Fitness Function. Feature Selection is the objective of the prediction model tocreate the underlying process of generalized data. The wide range of data like fault dataset, need the better objective function is obtained by feature selection, ranking, elimination and construction. In this paper, we focus on finding the fitness of the machine learning function which is used in the diagnostics of fault in the software for the better classification.

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