Results 261 to 270 of about 111,109 (312)

Process Design of Vinyl-Coated Metal Sheet Stamping for Prevention of Delamination and Wrinkling by DNN-Based Multi-Objective Optimization. [PDF]

Materials (Basel)
Kim MG, Ryu JC, Lee CJ, Jang JS, Ko DC.
europepmc   +1 more source

DCRDF-Net: A Dual-Channel Reverse-Distillation Fusion Network for 3D Industrial Anomaly Detection. [PDF]

Sensors (Basel)
Wang C, Chen J, Zhang H.
europepmc   +1 more source

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Cross-project smell-based defect prediction

Soft Computing, 2021
Defect prediction is a technique introduced to optimize the testing phase of the software development pipeline by predicting which components in the software may contain defects. Its methodology trains a classifier with data regarding a set of features measured on each component from the target software project to predict whether the component may be ...
Bruno Sotto-Mayor, Meir Kalech
openaire   +1 more source

Ensemble Based-Cross Project Defect Prediction

2021
In Software Testing, there are typically two ways to predict defects in the software—within-project defect prediction (WPDP) and cross project defect prediction (CPDP). In this research, we are using a hybrid model for cross project defect prediction. It is a two-phase model consisting of ensemble learning (EL) and genetic algorithm (GA) phase. For our
Rajni Jindal, Adil Ahmad, Anshuman Aditya   +2 more
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Local modeling approach for cross-project defect prediction

Intelligent Decision Technologies, 2022
Prediction approaches used for cross-project defect prediction (CPDP) are usually impractical because of high false alarms, or low detection rate. Instance based data filter techniques that improve the CPDP performance are time-consuming and each time a new test set arrives for prediction the entire filter procedure is repeated. We propose to use local
Bhat, Nayeem Ahmad, Farooq, Sheikh Umar
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Multi-objective Cross-Project Defect Prediction

2013 IEEE Sixth International Conference on Software Testing, Verification and Validation, 2013
Cross-project defect prediction is very appealing because (i) it allows predicting defects in projects for which the availability of data is limited, and (ii) it allows producing generalizable prediction models. However, existing research suggests that cross-project prediction is particularly challenging and, due to heterogeneity of projects ...
G. Canfora, A. De Lucia, M. Di Penta, OLIVETO, Rocco, A. Panichella, S. Panichella   +5 more
openaire   +2 more sources

A Framework for Homogeneous Cross-Project Defect Prediction

International Journal of Software Innovation, 2021
Often, the prior defect data of the same project is unavailable; researchers thought whether the defect data of the other projects can be used for prediction. This made cross project defect prediction an open research issue. In this approach, the training data often suffers from class imbalance problem.
Lipika Goel, Mayank Sharma, Sunil Kumar Khatri, D. Damodaran   +3 more
openaire   +1 more source