Deep semantic feature learning for software defect prediction
Software defect prediction, which predicts defective code regions, can assist developers in
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …
finding bugs and prioritizing their testing efforts. Traditional defect prediction features often …
Software defect prediction based on enhanced metaheuristic feature selection optimization and a hybrid deep neural network
K Zhu, S Ying, N Zhang, D Zhu - Journal of Systems and Software, 2021 - Elsevier
Software defect prediction aims to identify the potential defects of new software modules in
advance by constructing an effective prediction model. However, the model performance is …
advance by constructing an effective prediction model. However, the model performance is …
Large-scale intent analysis for identifying large-review-effort code changes
Context: Code changes to software occur due to various reasons such as bug fixing, new
feature addition, and code refactoring. Change intents have been studied for years to help …
feature addition, and code refactoring. Change intents have been studied for years to help …
Where is your app frustrating users?
User reviews of mobile apps provide a communication channel for developers to perceive
user satisfaction. Many app features that users have problems with are usually expressed by …
user satisfaction. Many app features that users have problems with are usually expressed by …
Images don't lie: Duplicate crowdtesting reports detection with screenshot information
Context: Crowdtesting is effective especially when it comes to the feedback on GUI systems,
or subjective opinions about features. Despite of this, we find crowdtesting reports are highly …
or subjective opinions about features. Despite of this, we find crowdtesting reports are highly …
Leveraging change intents for characterizing and identifying large-review-effort changes
Code changes to software occur due to various reasons such as bug fixing, new feature
addition, and code refactoring. In most existing studies, the intent of the change is rarely …
addition, and code refactoring. In most existing studies, the intent of the change is rarely …
Within‐project and cross‐project just‐in‐time defect prediction based on denoising autoencoder and convolutional neural network
K Zhu, N Zhang, S Ying, D Zhu - IET Software, 2020 - Wiley Online Library
Just‐in‐time defect prediction is an important and useful branch in software defect
prediction. At present, deep learning is a research hotspot in the field of artificial intelligence …
prediction. At present, deep learning is a research hotspot in the field of artificial intelligence …
Context-aware personalized crowdtesting task recommendation
Crowdsourced software testing (short for crowdtesting) is a special type of crowdsourcing. It
requires that crowdworkers master appropriate skill-sets and commit significant effort for …
requires that crowdworkers master appropriate skill-sets and commit significant effort for …
Improving crowd-supported gui testing with structural guidance
Crowd testing is an emerging practice in Graphical User Interface (GUI) testing, where
developers recruit a large number of crowd testers to test GUI features. It is often easier and …
developers recruit a large number of crowd testers to test GUI features. It is often easier and …
Context-and fairness-aware in-process crowdworker recommendation
Identifying and optimizing open participation is essential to the success of open software
development. Existing studies highlighted the importance of worker recommendation for …
development. Existing studies highlighted the importance of worker recommendation for …