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View article: FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks
FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks Open
Deep neural networks (DNNs) are being utilized in various aspects of our daily lives, including high-stakes decision-making applications that impact individuals. However, these systems reflect and amplify bias from the data used during tra…
View article: FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks
FairFLRep: Fairness aware fault localization and repair of Deep Neural Networks Open
Deep neural networks (DNNs) are being utilized in various aspects of our daily lives, including high-stakes decision-making applications that impact individuals. However, these systems reflect and amplify bias from the data used during tra…
View article: An Empirical Study of Testing Machine Learning in the Wild
An Empirical Study of Testing Machine Learning in the Wild Open
Background : Recently, machine and deep learning (ML/DL) algorithms have been increasingly adopted in many software systems. Due to their inductive nature, ensuring the quality of these systems remains a significant challenge for the resea…
View article: An empirical study of testing machine learning in the wild
An empirical study of testing machine learning in the wild Open
Recently, machine and deep learning (ML/DL) algorithms have been increasingly adopted in many software systems. Due to their inductive nature, ensuring the quality of these systems remains a significant challenge for the research community…
View article: Detection and Evaluation of bias-inducing Features in Machine learning
Detection and Evaluation of bias-inducing Features in Machine learning Open
The cause-to-effect analysis can help us decompose all the likely causes of a problem, such as an undesirable business situation or unintended harm to the individual(s). This implies that we can identify how the problems are inherited, ran…
View article: An Empirical Study of Challenges in Converting Deep Learning Models
An Empirical Study of Challenges in Converting Deep Learning Models Open
There is an increase in deploying Deep Learning (DL)-based software systems in real-world applications. Usually DL models are developed and trained using DL frameworks that have their own internal mechanisms/formats to represent and train …
View article: An Empirical Study on the Usage of Automated Machine Learning Tools
An Empirical Study on the Usage of Automated Machine Learning Tools Open
The popularity of automated machine learning (AutoML) tools in different domains has increased over the past few years. Machine learning (ML) practitioners use AutoML tools to automate and optimize the process of feature engineering, model…
View article: An Empirical Study of Challenges in Converting Deep Learning Models
An Empirical Study of Challenges in Converting Deep Learning Models Open
There is an increase in deploying Deep Learning (DL)-based software systems in real-world applications. Usually DL models are developed and trained using DL frameworks that have their own internal mechanisms/formats to represent and train …
View article: Studying the Practices of Deploying Machine Learning Projects on Docker
Studying the Practices of Deploying Machine Learning Projects on Docker Open
Docker is a containerization service that allows for convenient deployment of\nwebsites, databases, applications' APIs, and machine learning (ML) models with\na few lines of code. Studies have recently explored the use of Docker for\ndeplo…
View article: Technical Debts and Faults in Open-source Quantum Software Systems: An Empirical Study
Technical Debts and Faults in Open-source Quantum Software Systems: An Empirical Study Open
Quantum computing is a rapidly growing field attracting the interest of both researchers and software developers. Supported by its numerous open-source tools, developers can now build, test, or run their quantum algorithms. Although the ma…
View article: Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues
Understanding Quantum Software Engineering Challenges An Empirical Study on Stack Exchange Forums and GitHub Issues Open
With the advance in quantum computing, quantum software becomes critical for exploring the full potential of quantum computing systems. Recently, quantum software engineering (QSE) becomes an emerging area attracting more and more attentio…
View article: Studying the Practices of Deploying Machine Learning Projects on Docker
Studying the Practices of Deploying Machine Learning Projects on Docker Open
This repository contains the dataset for our study titled above: Below is the abstract: Docker is a containerization service that allows for convenient deployment of websites, databases, applications' APIs, and machine learning (ML) models…
View article: Studying the Practices of Deploying Machine Learning Projects on Docker
Studying the Practices of Deploying Machine Learning Projects on Docker Open
This repository contains the dataset for our study titled above: Below is the abstract: Docker is a containerization service that allows for convenient deployment of websites, databases, applications' APIs, and machine learning (ML) models…
View article: Reuse and maintenance practices among divergent forks in three software ecosystems
Reuse and maintenance practices among divergent forks in three software ecosystems Open
With the rise of social coding platforms that rely on distributed version control systems, software reuse is also on the rise. Many software developers leverage this reuse by creating variants through forking, to account for different cust…
View article: Are Multi-Language Design Smells Fault-Prone? An Empirical Study
Are Multi-Language Design Smells Fault-Prone? An Empirical Study Open
Nowadays, modern applications are developed using components written in different programming languages and technologies. The cost benefits of reuse and the advantages of each programming language are two main incentives behind the prolife…
View article: Are Multi-language Design Smells Prevalent? An Empirical Study.
Are Multi-language Design Smells Prevalent? An Empirical Study. Open
View article: Release Engineering Posts
Release Engineering Posts Open
This dataset was used for the study "Analysis of Release Engineering Topics - A Large-scale Study using Stackoverflow - "
View article: Release Engineering Posts
Release Engineering Posts Open
Release engineers are continuously required to de-liver high-quality software products to the end-user. As a result, modern software companies are proposing new changes in their delivery process that adapt to new technologies such as conti…
View article: Release Engineering Posts
Release Engineering Posts Open
Release engineers are continuously required to de-liver high-quality software products to the end-user. As a result, modern software companies are proposing new changes in their delivery process that adapt to new technologies such as conti…
View article: How Stable Are Eclipse Application Framework Internal Interfaces?
How Stable Are Eclipse Application Framework Internal Interfaces? Open
Eclipse framework provides two interfaces: stable interfaces (APIs) and unstable interfaces (non-APIs). Despite the non-APIs being discouraged and unsupported, their usage is not uncommon. Previous studies showed that applications using re…