{"id":749215,"date":"2021-05-27T11:18:38","date_gmt":"2021-05-27T18:18:38","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=749215"},"modified":"2021-05-27T11:23:11","modified_gmt":"2021-05-27T18:23:11","slug":"glinda-supporting-data-science-with-live-programming-guis-and-a-domain-specific-language","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/glinda-supporting-data-science-with-live-programming-guis-and-a-domain-specific-language\/","title":{"rendered":"Glinda: Supporting Data Science with Live Programming, GUIs and a Domain-specific Language"},"content":{"rendered":"

Researchers have explored several avenues to mitigate data scientists\u2019 frustrations with computational notebooks, including: (1) live programming, to keep notebook results consistent and up to date; (2) supplementing scripting with graphical user interfaces (GUIs), to improve ease of use; and (3) providing domain-specific languages (DSLs), to raise a script\u2019s level of abstraction. This paper introduces Glinda, which combines these three approaches by providing a live programming experience, with interactive results, for a domain-specific language for data science. The language\u2019s compiler uses an open-ended set of \u201crecipes\u201d to execute steps in the user\u2019s data science workflow. Each recipe is intended to combine the expressiveness of a written notation with the ease-of-use of a GUI. Live programming provides immediate feedback to a user\u2019s input, whether in the form of program edits or GUI gestures. In a qualitative evaluation with 12 professional data scientists, participants highly rated the live programming and interactive results. They found the language productive and sufficiently expressive and suggested opportunities to extend it.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers have explored several avenues to mitigate data scientists\u2019 frustrations with computational notebooks, including: (1) live programming, to keep notebook results consistent and up to date; (2) supplementing scripting with graphical user interfaces (GUIs), to improve ease of use; and (3) providing domain-specific languages (DSLs), to raise a script\u2019s level of abstraction. 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