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ASE 2020
Mon 21 - Fri 25 September 2020 Melbourne, Australia
Tue 22 Sep 2020 09:50 - 10:10 at Kangaroo - Formal Methods (2) Chair(s): Eunsuk Kang

Charts are commonly used for data visualization. Generating a chart usually involves performing data transformations, including data pre-processing and aggregation. These tasks can be cumbersome and time-consuming, even for experienced data scientists. Reproducing existing charts can also be a challenging task when information about data transformations is no longer available.

In this paper, we tackle the problem of recovering data transformations from existing charts. Given an input table and a chart, our goal is to automatically recover the data transformation program underlying the chart. We divide our approach into four steps: (1) data extraction, (2) candidate generation, (3) candidate ranking, and (4) candidate disambiguation. We implemented our approach in a tool called UnchartIt and evaluated it on a set of $50$ benchmarks from Kaggle. Experimental results show that UnchartIt successfully ranks the correct data transformation program in the top-10 in $92%$ of the instances. To disambiguate those programs, we use our new interactive disambiguation procedure, which successfully returns the correct program on 98% of the ambiguous instances by asking on average fewer than 2 questions to the user.

Tue 22 Sep
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09:10 - 10:10: Formal Methods (2)Research Papers at Kangaroo
Chair(s): Eunsuk KangCarnegie Mellon University, USA
09:10 - 09:30
Talk
Research Papers
Andreas StahlbauerUniversity of Passau, Christoph Fr├ĄdrichUniversity of Passau, Gordon FraserUniversity of Passau
09:30 - 09:50
Talk
Research Papers
Xingyu ZhaoHeriot-Watt University, Radu CalinescuUniversity of York, UK, Simos GerasimouUniversity of York, UK, Valentin RobuHeriot-Watt University, David FlynnHeriot-Watt University
Pre-print
09:50 - 10:10
Talk
Research Papers
Daniel RamosINESC-ID/IST, Universidade de Lisboa, Jorge PereiraINESC-ID/IST, Universidade de Lisboa, Ines LynceINESC-ID/IST, Universidade de Lisboa, Vasco ManquinhoINESC-ID/IST, Universidade de Lisboa, Ruben MartinsCarnegie Mellon University