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Filtering by: Alternative title ssim Data report 170 Degree Level Doctoral Resource Type Research Paper

Understanding Software-2.0: A Study of Machine Learning library usage and evolution

Creator:

Dilhara, Malinda, Ketkar, Ameya, and Dig, Danny

Abstract:

Enabled by a rich ecosystem of Machine Learning (ML) libraries, programming using learned models, i.e., Software-2.0, has gained substantial adoption. However, we do not know what challenges developers encounter when they use ML libraries. With this knowledge gap, researchers miss opportunities to contribute to new research directions, tool builders do...

Resource Type:

Research Paper

Full Text:

smaller components. In Software 2.0: Engineers amass training data and simply feed it into an ML algorithm