Kayur Patel, Naomi Bancroft, Steven M. Drucker, James Fogarty, Andrew J. Ko, James A. Landay
UIST '10 Proceedings of the 23nd annual ACM symposium on User interface software and technology
Summary:
This paper is about a new development envirnonment for machine learning called Gestalt. Where most programming environments focus on source code, Gestalt works with both source and data. Gestalt allows developers to create a classification pipeline, follow data through that pipeline, and offers easy transition between implementation and analysis. An experiment was conducted with this new environment, and a significant increase of bug detection and fixes was shown.
Discussion:
I think that this could be a very useful tool. When developing code, one of the hardest things is to find bugs, and if Gestalt makes it easier, I would like to give it a try. Also, when just looking at the code, it can be difficult to visualize what is going on, so it is important that the environment can transition easily.
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