Title :
Pseudogen: A Tool to Automatically Generate Pseudo-Code from Source Code
Author :
Hiroyuki Fudaba;Yusuke Oda;Koichi Akabe;Graham Neubig;Hideaki Hata;Sakriani Sakti;Tomoki Toda;Satoshi Nakamura
Author_Institution :
Nara Inst. of Sci. &
Abstract :
Understanding the behavior of source code written in an unfamiliar programming language is difficult. One way to aid understanding of difficult code is to add corresponding pseudo-code, which describes in detail the workings of the code in a natural language such as English. In spite of its usefulness, most source code does not have corresponding pseudo-code because it is tedious to create. This paper demonstrates a tool Pseudogen that makes it possible to automatically generate pseudo-code from source code using statistical machine translation (SMT). Pseudogen currently supports generation of English or Japanese pseudo-code from Python source code, and the SMT framework makes it easy for users to create new generators for their preferred source code/pseudo-code pairs.
Keywords :
"Computer languages","Natural languages","Generators","Syntactics","Training","Programming","Arrays"
Conference_Titel :
Automated Software Engineering (ASE), 2015 30th IEEE/ACM International Conference on
DOI :
10.1109/ASE.2015.107