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Deployment and performance monitoring of docker based federated learning framework for software defect prediction
There are significant challenges in machine learning models due to information security and data privacy issues. In traditional machine learning...
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Just-in-Time crash prediction for mobile apps
Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time. Hence, developers can take precautions to avoid defects when...
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Problems with SZZ and features: An empirical study of the state of practice of defect prediction data collection
ContextThe SZZ algorithm is the de facto standard for labeling bug fixing commits and finding inducing changes for defect prediction data. Recent...
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VDCNet: A Vulnerability Detection and Classification System in Cross-Project Scenarios
The existence of software vulnerabilities is the primary cause of most security incidents in cyberspace. Timely detection of potential...
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Deep Adversarial Learning Based Heterogeneous Defect Prediction
Cross-project defect prediction (CPDP) is a hot study that predicts defects in the new project by utilizing the model trained on the data from other...
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Adaptive recurrent neural network for software defect prediction with the aid of quantum theory- particle swarm optimization
With the proliferation of software programs, predicting defects has become a big concern. Therefore, to overcome this challenge, this research...
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Defect count prediction via metric-based convolutional neural network
With the increasing complexity and volume of the software, the number of defects in software modules is also increasing consistently, which affects...
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On the adoption and effects of source code reuse on defect proneness and maintenance effort
Software reusability mechanisms, like inheritance and delegation in Object-Oriented programming, are widely recognized as key instruments of software...
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Defect graph neural networks for materials discovery in high-temperature clean-energy applications
We present a graph neural network approach that fully automates the prediction of defect formation enthalpies for any crystallographic site from the...
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Cross Project Defect Prediction via Balanced Distribution Adaptation Based Transfer Learning
Defect prediction assists the rational allocation of testing resources by detecting the potentially defective software modules before releasing...
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Cross-Project Software Defect Prediction Based on Feature Selection and Transfer Learning
Cross-project software defect prediction solves the problem that traditional defect prediction can’t get enough data, but how to apply the model...
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Continuous build outcome prediction: an experimental evaluation and acceptance modelling
Continuous Build Outcome Prediction (CBOP) is a lightweight implementation of Continuous Defect Prediction (CDP). CBOP combines: 1) results of...
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Weighted software metrics aggregation and its application to defect prediction
It is a well-known practice in software engineering to aggregate software metrics to assess software artifacts for various purposes, such as their...
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A Software Vulnerability Prediction Model Using Traceable Code Patterns and Software Metrics
The goal of this research is to build a vulnerability prediction model to assist developers in evaluating the security of software systems during the...
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Continuous Defect Prediction in CI/CD Pipelines: A Machine Learning-Based Framework
Recent advances in information technology has led to an increasing number of applications to be developed and maintained daily by product teams....
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Does class size matter? An in-depth assessment of the effect of class size in software defect prediction
In the past 20 years, defect prediction studies have generally acknowledged the effect of class size on software prediction performance. To quantify...
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The impact of class imbalance techniques on crashing fault residence prediction models
Software crashes occur when the software program is executed wrongly or interrupted compulsively, which negatively impacts on user experience. Since...
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Bootstrap aggregation ensemble learning-based reliable approach for software defect prediction by using characterized code feature
To ensure software quality, software defect prediction plays a prominent role for the software developers and practitioners. Software defect...
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An adaptive incremental two-stage framework for crack defect detection
Stam** is the earliest and most important process in automobile manufacturing, significantly impacting the overall surface quality of automobiles....
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Searching for Bellwether Developers for Cross-Personalized Defect Prediction
Context: Recent progress in the use of commit data for software defect prediction has driven research on personalized defect prediction. An idea...