Stephen G. MacDonell
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View article: On the need to perform comprehensive evaluations of automated program repair benchmarks: Sorald case study
On the need to perform comprehensive evaluations of automated program repair benchmarks: Sorald case study Open
In supporting the development of high-quality software, especially necessary in the era of LLMs, automated program repair (APR) tools aim to improve code quality by automatically addressing violations detected by static analysis profilers.…
View article: MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud
MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud Open
Mobile cloud computing (MCC) is a technological paradigm for providing services to mobile device (MD) users. A compromised MD may cause harm to both its user and to other MCC customers. This study explores the use of machine learning (ML) …
View article: MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud
MINDPRES: A Hybrid Prototype System for Comprehensive Data Protection in the User Layer of the Mobile Cloud Open
Mobile cloud computing (MCC) is a prevailing technological paradigm for providing services to customers who have access to mobile devices (MD). Security compromises at the user layer of MCC may cause harm to the MD user as well as to other…
View article: A Risk Assessment Framework for Mobile Apps in Mobile Cloud Computing Environments
A Risk Assessment Framework for Mobile Apps in Mobile Cloud Computing Environments Open
Mobile devices (MDs) are used by mobile cloud computing (MCC) customers and by other users because of their portability, robust connectivity, and ability to house and operate third-party applications (apps). However, the apps installed on …
View article: A Risk Assessment Framework for Mobile Apps in Mobile Cloud Computing Environments
A Risk Assessment Framework for Mobile Apps in Mobile Cloud Computing Environments Open
Mobile devices (MD) are used by mobile cloud computing (MCC) customers users because of their 11 portability and robust connectivity and the ability to house and operate third-party applications 12 (apps). However, the apps installed on a …
View article: Just-in-Time crash prediction for mobile apps
Just-in-Time crash prediction for mobile apps Open
Just-In-Time (JIT) defect prediction aims to identify defects early, at commit time. Hence, developers can take precautions to avoid defects when the code changes are still fresh in their minds. However, the utility of JIT defect predictio…
View article: Improving transfer learning for software cross-project defect prediction
Improving transfer learning for software cross-project defect prediction Open
Software cross-project defect prediction (CPDP) makes use of cross-project (CP) data to overcome the lack of data necessary to train well-performing software defect prediction (SDP) classifiers in the early stage of new software projects. …
View article: Soil texture prediction with automated deep convolutional neural networks and population-based learning
Soil texture prediction with automated deep convolutional neural networks and population-based learning Open
Convolutional neural networks (CNNs) performance requires tuning of network architectures, which requires machine learning knowledge and significant time and effort. Thus, modern deep CNN in soil spectroscopy faces a major barrier as a res…
View article: Data Extraction and Preprocessing of code snippets on Stack Overflow for Static Code Analysis
Data Extraction and Preprocessing of code snippets on Stack Overflow for Static Code Analysis Open
Stack Overflow is noteworthy in its value to software practitioners. However, few formal datasets exist to facilitate proper benchmarking research. Our study catalogues the data extraction process to collect massive amounts of Java code sn…
View article: Improving Transfer Learning for Cross Project Defect Prediction
Improving Transfer Learning for Cross Project Defect Prediction Open
—Cross-project defect prediction (CPDP) makes use of cross-project (CP) data to overcome the lack of data necessary to train well-performing software defect prediction (SDP) classifiers in the early stage of new software projects. Since th…
View article: Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence Open
Experimental results from the paper titled "Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence"
View article: Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence Open
Experimental results from the paper titled "Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence"
View article: Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence Open
Experimental results from the paper titled "Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence"
View article: Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence Open
Experimental results from the paper titled "Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence"
View article: Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence
Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence Open
Experimental results from the paper titled "Negative Transfer in Cross Project Defect Prediction: Effect of Domain Divergence"
View article: Quality Assurance in the Context of Contemporary Software Practice
Quality Assurance in the Context of Contemporary Software Practice Open
We review the literature on the nature of quality assurance in the context of comnplex systems developed using iterative and incremental approaches.
View article: Improving Model Selection in Deep Supervised Transfer Learning Under Homogeneous Setting
Improving Model Selection in Deep Supervised Transfer Learning Under Homogeneous Setting Open
In traditional machine learning environments, the use of non-parametric error estimation to set the discriminative threshold of a classifier to achieve the best accuracy is very effective. This method is not effective in a transfer learnin…
View article: Improving Model Selection in Deep Supervised Transfer Learning Under Homogeneous Setting
Improving Model Selection in Deep Supervised Transfer Learning Under Homogeneous Setting Open
In traditional machine learning environments, the use of non-parametric error estimation to set the discriminative threshold of a classifier to achieve the best accuracy is very effective. This method is not effective in a transfer learnin…
View article: How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package)
How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality differed over time? Research and practice viewpoints (Replication package)
How have views on Software Quality differed over time? Research and practice viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality shifted? Research and practice viewpoints (Replication package)
How have views on Software Quality shifted? Research and practice viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality shifted? Research and practice viewpoints (Replication package)
How have views on Software Quality shifted? Research and practice viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality differed over time? Research and practice viewpoints (Replication package)
How have views on Software Quality differed over time? Research and practice viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality differed over time? Research and practice viewpoints (Replication package)
How have views on Software Quality differed over time? Research and practice viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package)
How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package)
How have views on Software Quality shifted: theoretical and practical viewpoints (Replication package) Open
Theoretical and practical viewpoints on the quality of code snippets.
View article: Improving Transfer Learning for Cross Project Defect Prediction
Improving Transfer Learning for Cross Project Defect Prediction Open
—Cross-project defect prediction (CPDP) makes use of cross-project (CP) data to overcome the lack of data necessary to train well-performing software defect prediction (SDP) classifiers in the early stage of new software projects. Since th…
View article: Improving Transfer Learning for Cross Project Defect Prediction
Improving Transfer Learning for Cross Project Defect Prediction Open
—Cross-project defect prediction (CPDP) makes use of cross-project (CP) data to overcome the lack of data necessary to train well-performing software defect prediction (SDP) classifiers in the early stage of new software projects. Since th…