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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 Kang Carnegie Mellon University, USA
Verified from Scratch: Program Analysis for Learners' Programs
Research Papers
Andreas Stahlbauer University of Passau, Christoph Fr├Ądrich University of Passau, Gordon Fraser University of Passau
Interval Change-Point Detection for Runtime Probabilistic Model Checking
Research Papers
Xingyu Zhao Heriot-Watt University, Radu Calinescu University of York, UK, Simos Gerasimou University of York, UK, Valentin Robu Heriot-Watt University, David Flynn Heriot-Watt University
UnchartIt: An Interactive Framework for Program Recovery from Charts
Research Papers
Daniel Ramos INESC-ID/IST, Universidade de Lisboa, Jorge Pereira INESC-ID/IST, Universidade de Lisboa, Ines Lynce INESC-ID/IST, Universidade de Lisboa, Vasco Manquinho INESC-ID/IST, Universidade de Lisboa, Ruben Martins Carnegie Mellon University