A ground-truth dataset and classification model for detecting bots in GitHub issue and PR comments
Bots are frequently used in Github repositories to automate repetitive activities that are part
of the distributed software development process. They communicate with human actors …
of the distributed software development process. They communicate with human actors …
Performance analysis of feature selection methods in software defect prediction: a search method approach
Software Defect Prediction (SDP) models are built using software metrics derived from
software systems. The quality of SDP models depends largely on the quality of software …
software systems. The quality of SDP models depends largely on the quality of software …
Value-cognitive boosting with a support vector machine for cross-project defect prediction
It is well-known that software defect prediction is one of the most important tasks for software
quality improvement. The use of defect predictors allows test engineers to focus on defective …
quality improvement. The use of defect predictors allows test engineers to focus on defective …
A transfer cost-sensitive boosting approach for cross-project defect prediction
Software defect prediction has been regarded as one of the crucial tasks to improve software
quality by effectively allocating valuable resources to fault-prone modules. It is necessary to …
quality by effectively allocating valuable resources to fault-prone modules. It is necessary to …
A hybrid instance selection using nearest-neighbor for cross-project defect prediction
Software defect prediction (SDP) is an active research field in software engineering to
identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively …
identify defect-prone modules. Thanks to SDP, limited testing resources can be effectively …
Early prediction of merged code changes to prioritize reviewing tasks
Abstract Modern Code Review (MCR) has been widely used by open source and proprietary
software projects. Inspecting code changes consumes reviewers much time and effort since …
software projects. Inspecting code changes consumes reviewers much time and effort since …
A decision tree logic based recommendation system to select software fault prediction techniques
SS Rathore, S Kumar - Computing, 2017 - Springer
Identifying a reliable fault prediction technique is the key requirement for building effective
fault prediction model. It has been found that the performance of fault prediction techniques …
fault prediction model. It has been found that the performance of fault prediction techniques …
Semi-supervised deep fuzzy C-mean clustering for imbalanced multi-class classification
Semi-supervised learning has been successfully connected in the research fields of
machine learning such as data mining and dynamic data analysis. Imbalance class learning …
machine learning such as data mining and dynamic data analysis. Imbalance class learning …
[PDF][PDF] Software defect prediction: analysis of class imbalance and performance stability
The performance of prediction models in software defect prediction depends on the quality
of datasets used for training such models. Class imbalance is one of data quality problems …
of datasets used for training such models. Class imbalance is one of data quality problems …
Parameter tuning in KNN for software defect prediction: an empirical analysis
MA Mabayoje, AO Balogun, HA Jibril… - Jurnal Teknologi dan …, 2019 - jtsiskom.undip.ac.id
Abstract Software Defect Prediction (SDP) provides insights that can help software teams to
allocate their limited resources in developing software systems. It predicts likely defective …
allocate their limited resources in developing software systems. It predicts likely defective …