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A systematic literature review on fault prediction performance in software engineering
Background: The accurate prediction of where faults are likely to occur in code can help
direct test effort, reduce costs, and improve the quality of software. Objective: We investigate …
direct test effort, reduce costs, and improve the quality of software. Objective: We investigate …
An empirical comparison of model validation techniques for defect prediction models
Defect prediction models help software quality assurance teams to allocate their limited
resources to the most defect-prone modules. Model validation techniques, such as-fold …
resources to the most defect-prone modules. Model validation techniques, such as-fold …
[HTML][HTML] Comparison of random forest and gradient boosting machine models for predicting demolition waste based on small datasets and categorical variables
Construction and demolition waste (DW) generation information has been recognized as a
tool for providing useful information for waste management. Recently, numerous …
tool for providing useful information for waste management. Recently, numerous …
Is" better data" better than" better data miners"? on the benefits of tuning SMOTE for defect prediction
We report and fix an important systematic error in prior studies that ranked classifiers for
software analytics. Those studies did not (a) assess classifiers on multiple criteria and they …
software analytics. Those studies did not (a) assess classifiers on multiple criteria and they …
Software defect prediction: do different classifiers find the same defects?
During the last 10 years, hundreds of different defect prediction models have been
published. The performance of the classifiers used in these models is reported to be similar …
published. The performance of the classifiers used in these models is reported to be similar …
Choosing software metrics for defect prediction: an investigation on feature selection techniques
The selection of software metrics for building software quality prediction models is a search‐
based software engineering problem. An exhaustive search for such metrics is usually not …
based software engineering problem. An exhaustive search for such metrics is usually not …
Software defect prediction using supervised machine learning and ensemble techniques: a comparative study
An essential objective of software development is to locate and fix defects ahead of
schedule that could be expected under diverse circumstances. Many software development …
schedule that could be expected under diverse circumstances. Many software development …
[HTML][HTML] Development of a prediction model for demolition waste generation using a random forest algorithm based on small datasets
Recently, artificial intelligence (AI) technologies have been employed to predict construction
and demolition (C&D) waste generation. However, most studies have used machine …
and demolition (C&D) waste generation. However, most studies have used machine …
Attribute selection and imbalanced data: Problems in software defect prediction
The data mining and machine learning community is often faced with two key problems:
working with imbalanced data and selecting the best features for machine learning. This …
working with imbalanced data and selecting the best features for machine learning. This …
Graph neural network for source code defect prediction
Predicting defective software modules before testing is a useful operation that ensures that
the time and cost of software testing can be reduced. In recent years, several models have …
the time and cost of software testing can be reduced. In recent years, several models have …