We consider the task of mapping pseudocode to executable code, assuming a one-to-one
correspondence between lines of pseudocode and lines of code. Given test cases as a …

Pseudo-code written in natural language can aid the comprehension of source code in
unfamiliar programming languages. However, the great majority of source code has no …

The task of generating code solutions for a given programming problem can benefit from the
use of pre-trained language models such as Codex, which can produce multiple diverse …

In models to generate program source code from natural language, representing this code in
a tree structure has been a common approach. However, existing methods often fail to …

We present a neural program synthesis approach integrating components which write,
execute, and assess code to navigate the search space of possible programs. We equip the …

Pseudo-code written by natural language is helpful for novice developers' program
comprehension. However, writing such pseudo-code is time-consuming and laborious …

Publicly available source-code libraries are continuously growing and changing. This makes
it impossible for models of code to keep current with all available APIs by simply training …

We present a Neural Program Search, an algorithm to generate programs from natural
language description and a small number of input/output examples. The algorithm combines …

We study the problem of generating source code in a strongly typed, Java-like programming
language, given a label (for example a set of API calls or types) carrying a small amount of …

Our goal is to build systems which write code automatically from the kinds of specifications
humans can most easily provide, such as examples and natural language instruction. The …