Traditional software development activities (like editing, testing, debugging, and others) often need to be carried out by individuals who are not typical software developers. Tools as diverse as spreadsheets, Jupyter notebooks, and deep learning frameworks all empower users to create solutions that have much in common with traditional software. Unfortunately, typical software tools do not directly translate into these new development processes. In this webinar led by Partner Researcher Dr. Ben Zorn, follow the path of the revolution that empowers more people to easily leverage computational resources for problem solving. You will examine the incredible opportunities and technical challenges of empowering users to quickly build correct and meaningful spreadsheets. The focus here includes recent efforts to combine spatial analysis, statistical analysis, and deep learning to find bugs in spreadsheets. You will also find out how AI is advancing data programming as we know it. Finally, you will learn about two exciting projects from Microsoft researchers. In the ExceLint project, with Daniel Barowy and Emery Berger, researchers use a combination of program, spatial, and statistical analysis to highlight unusual anomalous formulas in spreadsheets. In the Jura project, with Saswat Padhi, Alex Polozov, and Dany Rouhana, researchers apply deep neural networks trained on thousands of spreadsheets to predict properties of sheets, including where tables are located and whether cells should contain formulas.<\/p>\n
Together, you will explore:<\/p>\n
Resource list:<\/strong><\/p>\n *This on-demand webinar features a previously recorded Q&A session and open captioning.<\/p>\n This webinar originally aired on March 09, 2020<\/p>\n\n