10 citations · 12 across the 5 of their papers we have counts for
5 papers
Adaptoring: Adapter Generation to Provide an Alternative API for a Library
Lars Reimann, Günter Kniesel-Wünsche
Third-party libraries are a cornerstone of fast application development. To enable efficient use, libraries must provide a well-designed API. An obscure API instead slows down the…
An Alternative to Cells for Selective Execution of Data Science Pipelines
Lars Reimann, Günter Kniesel-Wünsche
Data Scientists often use notebooks to develop Data Science (DS) pipelines, particularly since they allow to selectively execute parts of the pipeline. However, notebooks for DS ha…
Safe-DS: A Domain Specific Language to Make Data Science Safe
Lars Reimann, Günter Kniesel-Wünsche
Due to the long runtime of Data Science (DS) pipelines, even small programming mistakes can be very costly, if they are not detected statically. However, even basic static type che…
Improving the Learnability of Machine Learning APIs by Semi-Automated API Wrapping
Lars Reimann, Günter Kniesel-Wünsche
A major hurdle for students and professional software developers who want to enter the world of machine learning (ML), is mastering not just the scientific background but also the…
Achieving Guidance in Applied Machine Learning through Software Engineering Techniques
Lars Reimann, Günter Kniesel-Wünsche
Development of machine learning (ML) applications is hard. Producing successful applications requires, among others, being deeply familiar with a variety of complex and quickly evo…