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Data-centric disambiguation for data transformation with programming-by-example
Author(s) -
Minori Narita,
Nolwenn Maudet,
Yi Lü,
Takeo Igarashi
Publication year - 2021
Publication title -
univoak (4 institutions : université de strasbourg, université de haute alsace, insa strasbourg, bibliothèque nationale et universitaire de strasbourg)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/3397481.3450680
Subject(s) - computer science , generality , ambiguity , data transformation , transformation (genetics) , completeness (order theory) , process (computing) , focus (optics) , visualization , set (abstract data type) , data mining , program transformation , model transformation , data visualization , programming language , information retrieval , artificial intelligence , data warehouse , psychology , mathematical analysis , biochemistry , chemistry , physics , mathematics , consistency (knowledge bases) , gene , optics , psychotherapist
Programming-by-example (PBE), can be a powerful tool to reduce manual work in repetitive data transformation tasks. However, few examples often leave ambiguity and may cause undesirable data transformation by the system. This ambiguity can be resolved by allowing the user to directly edit the synthesized programs; however, this is difficult for non-programmers. Here, we present a novel approach: data-centric disambiguation for data transformation, where users resolve the ambiguity in data transformation by examining and modifying the output rather than the program. The key idea is to focus on the given set of data the user wants to transform instead of pursuing the synthesized program’s generality or completeness. Our system provides visualization and interaction methods that allow users to efficiently examine and fix the transformed outputs, which is much simpler than understanding and modifying the program itself. The user study suggests that our system can successfully help non-programmers to more easily and efficiently process data.

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