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Found 7 papers, 2 papers with code
An Empirical Study on Bugs Inside PyTorch: A Replication Study
Software systems are increasingly relying on deep learning components, due to their remarkable capability of identifying complex data patterns and powering intelligent behaviour.
Can Ensembling Pre-processing Algorithms Lead to Better Machine Learning Fairness?
As machine learning (ML) systems get adopted in more critical areas, it has become increasingly crucial to address the bias that could occur in these systems.
The Present and Future of Bots in Software Engineering
We are witnessing a massive adoption of software engineering bots, applications that react to events triggered by tools and messages posted by users and run automated tasks in response, in a variety of domains.
A Machine Learning Approach to Improve the Detection of CI Skip Commits
A key facilitator of CI is to automatically build and run tests whenever a new commit is submitted/pushed.
A Comparison of Natural Language Understanding Platforms for Chatbots in Software Engineering
Our results provide guidance to software engineering practitioners when deciding which NLU to use in their chatbots.
Breaking Type Safety in Go: An Empirical Study on the Usage of the unsafe Package
Our findings can be used to understand how and why developers break type-safety in Go, and help motivate further tools and language development that could make the usage of unsafe in Go even safer.
Subject Cross Validation in Human Activity Recognition
We conclude that Human Activity Recognition systems should be evaluated by Subject Cross Validation, and that overlapping windows are not worth their extra computational cost.
