Learning to Map Natural Language to General Purpose Source Code

Models that map natural language (NL) to source code in general purpose languages such as Java, Python, and SQL find utility amongst two main audiences viz. developers who can manipulate the generated code, and non-expert users who directly see the output of execution. Developing these models is challenging because of contextual dependencies of the target code, the lack of alignment between NL and code tokens, syntactic and semantic requirements of the target code, and the prohibitively expensive cost of an