Our first GSR talk+tutorial is on Feburary 12th, Tuesday, 3:30pm in Fitzpatrick 247C.
Coffee and snacks provided!
Submit questions for the tutorial here!
Hope to see you all there!
Growing Pains in Library Adoptions: An Exploration of GitHub Commit Logs
When a group of people attempts to understand new information, struggle ensues as various ideas compete for attention. Steep learning curves are surmounted as teams learn together. To understand how these team dynamics play out in technical fields, we explore Github logs, which provide a complete change history of software repositories. In these repositories, we observe code additions, which represent successfully implemented ideas, and code deletions, which represent ideas that have failed or been superseded. By examining the patterns between these commit types, we can begin to understand how teams adopt new information. We specifically study what happens after a software library is adopted by a project, \ie, when a library is used for the first time in the project. We find that a variety of factors, including team size, library popularity, and prevalence on Stack Overflow are associated with how quickly teams learn and successfully adopt new software libraries.
Pamela Bilo Thomas is a PhD student at University of Notre Dame working with Dr. Tim Weninger. She received a master’s degree in computer science from IU in 2013, and a BA in mathematics in 2011. Her current research focuses on how people change behavior and learn new information.
Green text on black: How to efficiently use the command line
So you log into the CRC and then? In this tutorial I will quickly explain the basics of the command line, and give an overview of the important things on the CRC. The first part will introduce to bash, my shell of choice, followed by neat tricks and cool one-liners. I will also introduce how to use GPU resources on the CRC respectfully. This tutorial will be lead by example.
Martin Imre is a third-yeard PhD student at the University of Notre Dame, working with Dr. Chaoli Wang on High Performance Computing and Scientific Visualization. His main area of research is isosurface selection for volume visualization and analysis, and graph visualization. He has completed a research internship at Argonne National Laboratory in summer 2018. Currently he is using deep learning techniques in visualization research. He received my BSc (2014) and MSc (2016) in Software Engineering at the Vienna University of Technology. During his Master’s program, he conducted research at the VRVis Research Center in Vienna and continued acquiring experience during a research internship at the University of California, Irvine. He is a Linux enthusiast and uses bash several hours per day.