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ASE 2021
Sun 14 - Sat 20 November 2021 Australia
Wed 17 Nov 2021 08:20 - 08:40 at Kangaroo - Bugs I Chair(s): Elena Sherman

Data scientists reportedly spend 60 to 80 percent of their time in their daily routines on data wrangling, i.e. cleaning data and extracting features. However, data wrangling code is often repetitive and error-prone to write. Moreover, it is easy to introduce subtle bugs when reusing and adopting existing code, which result not in crashes but reduce model quality. To support data scientists with data wrangling, we present a technique to generate interactive documentation for data wrangling code. We use (1) program synthesis techniques to automatically summarize data transformations and (2) test case selection techniques to purposefully select representative examples from the data based on execution information collected with tailored dynamic program analysis. We demonstrate that a JupyterLab extension with our technique can provide documentation for many cells in popular notebooks and find in a user study that users with our plugin are faster and more effective at finding realistic bugs in data wrangling code.

Wed 17 Nov

Displayed time zone: Hobart change

08:00 - 09:00
Bugs IResearch Papers / Industry Showcase / Tool Demonstrations at Kangaroo
Chair(s): Elena Sherman Boise State University
Research paper
On the Real-World Effectiveness of Static Bug Detectors at Finding Null Pointer Exceptions
Research Papers
David A Tomassi University of California, Davis, Cindy Rubio-González University of California at Davis
Subtle Bugs Everywhere: Generating Documentation for Data Wrangling Code
Research Papers
Chenyang Yang Peking University, Shurui Zhou University of Toronto, Jin L.C. Guo McGill University, Christian Kästner Carnegie Mellon University
Reducing Time-To-Fix For Fuzzer Bugs
Industry Showcase
Rui Abreu Faculty of Engineering, University of Porto, Portugal, Franjo Ivančić Google, Filip Niksic Google, Hadi Ravanbakhsh Google, Ramesh Viswanathan Google
Shaker: a Tool for Detecting More Flaky Tests Faster
Tool Demonstrations
Marcello Cordeiro Federal University of Pernambuco, Denini Silva Federal University of Pernambuco, Leopoldo Teixeira Federal University of Pernambuco, Breno Miranda Federal University of Pernambuco, Marcelo d'Amorim Federal University of Pernambuco
Link to publication