Increasingly software plays a role in every aspect of our lives, from managing Covid-19 and our finances, to interacting with other humans in education, work, and entertainment. There are critical shortages of software developers and experts across the world. With large numbers of services and apps in popular programming languages and over 200 billion lines of mission critical legacy COBOL code, having methods to analyze, develop, and maintain software in more automated ways is essential for progress. As a step along the way to automation, join the challenge to find programs that perform similar tasks. The team that makes the best prediction wins. The challenge is based on an extract from Project CodeNet which is a large-scale dataset with approximately 14 million code samples, each of which is an intended solution to one of 4000 coding problems.
Researchers David Kung, Ulrich Finkler, Vladimir Zolotov, Lindsey Decker will provide an overview for the dataset, and the challenge. They’ll also show you how to get started and explain how you can submit your predictions to the leaderboard. They’ll answer any questions too. This session is the same as Introduction 1 but may cover topics that were not included in Introduction 1
Contestants should be familiar with PyTorch or TensorFlow.
More information – http://ibm.biz/cfcsc-codenet. Do join us.