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Aug 11, 2024 · It will look at how defects can be predicted in a software during the testing phase with the aid of artificial intelligence and machine learning ...
In this paper we empirically evaluate the effectiveness of auto-sklearn in predicting the number of defects in software modules. In the experiment, we used ...
An Experimental Analysis on Automated Machine Learning for Software Defect Prediction. Conference Paper. Jun 2024. Márcio Basgalupp · Rodrigo C ...
A systematic literature review on software defect prediction using artificial intelligence: Datasets, Data Validation Methods, Approaches, and Tools
Mar 21, 2023 · We examined various known ML techniques and optimized ML techniques on a freely available data set. The purpose of the research was to improve the model ...
This paper introduces an efficient software failure prediction technique using hybrid machine learning algorithms.
Video for An Experimental Analysis on Automated Machine Learning for Software Defect Prediction.
Duration: 17:40
Posted: Dec 3, 2014
Missing: Experimental | Show results with:Experimental
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The results showed that a combination of ML algorithms could be used effectively to predict software defects, and the SMOreg classifier scored the best ...
The purpose of this study is to systematically identify, analyze, summarize, and synthesize the current state of the utilization of DL algorithms for SDP in the ...
One of the most notable techniques focuses on defect prediction using machine learning methods, which could support developers in handling these defects.