Deep Representations for Software Engineering

Deep learning subsumes algorithms that automatically learn compositional representations. The ability of these models to generalize well has ushered in tremendous advances in many fields. We propose that software engineering (SE) research is a unique opportunity to use these transformative approaches. Our research examines applications of deep architectures such as recurrent neural networks and stacked restricted Boltzmann machines to SE tasks.