Many software defect prediction datasets, methods and frameworks are published disparate and complex, thus a comprehensive picture of the current state of defect prediction research that exists is missing. This literature review aims to identify and analyze the research trends, datasets, methods and frameworks used in software defect prediction research betweeen 20. Simulated Annealing Neural Network for Software Failure Prediction. Software Fault Prediction Using Quad Tree-Based K-Means Clustering Algorithm.
However, remote access to EBSCO's databases from non-subscribing institutions is not allowed if the purpose of the use is for commercial gain through cost reduction or avoidance for a non-subscribing institution.
ORCID i D Dian Nuswantoro Indonesia Romi Satria Wahono. D in Software Engineering and Machine Learning from Universiti Teknikal Malaysia Melaka. IEEE Transactions on Evolutionary Computation, 7(6), 561–575.
In addition, 64.79% of the research studies used public datasets and 35.21% of the research studies used private datasets.
Nineteen different methods have been applied to predict software defects.
Expert Systems with Applications, 36(4), 7346–7354.
A systematic review of software fault prediction studies.
Feature selection has been applied to these combinations when models are performing particularly well.
Conclusion: The methodology used to build models seems to be influential to predictive performance.
The results of this research also identified three frameworks that are highly cited and therefore influential in the software defect prediction field.
Expert Systems with Applications, 38(4), 4626–4636.
Comments A Systematic Literature Review On Fault Prediction Performance In Software Engineering
A Systematic Literature Review of Software Defect Prediction.
International Journal of Software Engineering and Its Applications, 64. Bibi, S. A Systematic Literature Review on Fault Prediction Performance in Software.…
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Department of Computer Science and Engineering, Advanced. Abstract Software defect prediction has been one of the key areas of exploration in the domain of. Keywords defect; machine learning; systematic literature mapping;. Does the study clearly define the performance parameters used?…
Taxonomy of machine learning algorithms in software fault.
Catal C, Diri BA systematic review of software fault prediction studies. SA systematic literature review on fault prediction performance in software engineering.…
PDF A Systematic Review of Fault Prediction Performance in.
Article PDF Available in IEEE Transactions on Software Engineering 38991. MethodWe used a systematic literature review to identify 208 fault prediction.…
A Systematic Literature Review on Software Fault Prediction.
International Research Journal of Engineering and Technology IRJET e-ISSN 2395 -0056. Volume 04. A Systematic Literature Review on Software Fault Prediction and Fault. Tolerance. Performance Evaluation Metrics for Software Fault.…
Evaluating software defect prediction performance an. - arXiv
Such as class distribution sampling, evaluation metrics, and testing procedures. The new. The literature shows that many benchmarking studies use machine learning. In our new benchmarking study, we also include datasets. Software defect predictions generated by classifiers should be assessed in terms of accuracy.…
A systematic literature review on fault prediction.
A systematic literature review on fault prediction performance in software engineering Hall, T. and Beecham, S. and Bowes, D. and Gray, D. and Counsell, S. 2012 A systematic literature review on fault prediction performance in software engineering.…
A Systematic Literature Review on Fault Prediction.
A Systematic Literature Review on Fault Prediction Performance in Software Engineering. Abstract Background The accurate prediction of.…
A Systematic Review of Fault Prediction Performance in.
The aim of this systematic literature review SLR is to analyse the models used to predict faults in source code. Our analysis based on the research questions in Table 1.…