[HTML][HTML] 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 …
Researcher bias: The use of machine learning in software defect prediction
Background. The ability to predict defect-prone software components would be valuable.
Consequently, there have been many empirical studies to evaluate the performance of …
Consequently, there have been many empirical studies to evaluate the performance of …
Building an ensemble for software defect prediction based on diversity selection
Background: Ensemble techniques have gained attention in various scientific fields. Defect
prediction researchers have investigated many state-of-the-art ensemble models and …
prediction researchers have investigated many state-of-the-art ensemble models and …
Benchmarking classification models for software defect prediction: A proposed framework and novel findings
Software defect prediction strives to improve software quality and testing efficiency by
constructing predictive classification models from code attributes to enable a timely …
constructing predictive classification models from code attributes to enable a timely …
Assessing software defection prediction performance: Why using the Matthews correlation coefficient matters
J Yao, M Shepperd - Proceedings of the 24th International Conference …, 2020 - dl.acm.org
Context: There is considerable diversity in the range and design of computational
experiments to assess classifiers for software defect prediction. This is particularly so …
experiments to assess classifiers for software defect prediction. This is particularly so …
Evaluating defect prediction approaches: a benchmark and an extensive comparison
Reliably predicting software defects is one of the holy grails of software engineering.
Researchers have devised and implemented a plethora of defect/bug prediction approaches …
Researchers have devised and implemented a plethora of defect/bug prediction approaches …
The impact of using biased performance metrics on software defect prediction research
J Yao, M Shepperd - Information and Software Technology, 2021 - Elsevier
Context: Software engineering researchers have undertaken many experiments
investigating the potential of software defect prediction algorithms. Unfortunately some …
investigating the potential of software defect prediction algorithms. Unfortunately some …
[HTML][HTML] Problems with SZZ and features: An empirical study of the state of practice of defect prediction data collection
Context The SZZ algorithm is the de facto standard for labeling bug fixing commits and
finding inducing changes for defect prediction data. Recent research uncovered potential …
finding inducing changes for defect prediction data. Recent research uncovered potential …
Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem
Software development projects inevitably accumulate defects throughout the development
process. Due to the high cost that defects can incur, careful consideration is crucial when …
process. Due to the high cost that defects can incur, careful consideration is crucial when …
The impact of feature reduction techniques on defect prediction models
Defect prediction is an important task for preserving software quality. Most prior work on
defect prediction uses software features, such as the number of lines of code, to predict …
defect prediction uses software features, such as the number of lines of code, to predict …