Automating Software Engineering with Machine Learning

Abstract

Software plays a crucial role in our everyday lives. The scarcity of skilled software engineers has become a bottleneck in delivering better software at scale. Can we automate software engineering to help improve developer productivity and software quality? Can we take advantage of massive codebases to learn about building correct and scalable software? In this talk, I will present some recent advances in automated software engineering using machine learning. Along the way, I will relate the data-driven techniques to traditional, algorithmic program analysis techniques. I will discuss representative deep learning methods to analyze and synthesize source code. Even though we are witnessing exciting new advances in machine learning for software engineering, we shall reflect on what challenges remain and the way forward.