Research at the intersection of machine learning, programming languages, and software
engineering has recently taken important steps in proposing learnable probabilistic models …

Deep Learning (DL) techniques for Natural Language Processing have been evolving
remarkably fast. Recently, the DL advances in language modeling, machine translation, and …

Evaluation metrics play a vital role in the growth of an area as it defines the standard of
distinguishing between good and bad models. In the area of code synthesis, the commonly …

We present Spider, a large-scale, complex and cross-domain semantic parsing and text-to-
SQL dataset annotated by 11 college students. It consists of 10,181 questions and 5,693 …

A transcompiler, also known as source-to-source translator, is a system that converts source
code from a high-level programming language (such as C++ or Python) to another …

The ability to generate natural language sequences from source code snippets has a variety
of applications such as code summarization, documentation, and retrieval. Sequence-to …

We present a neural model for representing snippets of code as continuous distributed
vectors (``code embeddings''). The main idea is to represent a code snippet as a single fixed …

During software maintenance, code comments help developers comprehend programs and
reduce additional time spent on reading and navigating source code. Unfortunately, these …

Code summarization provides a high level natural language description of the function
performed by code, as it can benefit the software maintenance, code categorization and …

We consider the problem of parsing natural language descriptions into source code written
in a general-purpose programming language like Python. Existing data-driven methods treat …