Abstract: Understanding a large number of source code is a big challenge for software development teams in software maintenance process. Using topic models is a promising way to automatically discover feature and structure from textual software assets, and thus support developers comprehending programs on software maintenance. To explore the application of applying topic modeling to software engineering practice, we proposed JSEA (Java Software Engineers Assistant), an interactive program comprehension tool adopting LDA-based topic modeling, to support developers during performing software maintenance tasks. JSEA utilizes essential information automatically generated from Java source code to establish a project overview and to bring search capability for software engineers. The results of our preliminary experimentation suggest the practicality of JSEA.

Tianxia Wang and Yan Liu, “JSEA: A Program Comprehension Tool Adopting LDA-based Topic Modeling” International Journal of Advanced Computer Science and Applications(IJACSA), 8(3), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080359

@article{Wang2017,
title = {JSEA: A Program Comprehension Tool Adopting LDA-based Topic Modeling},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080359},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080359},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {3},
author = {Tianxia Wang and Yan Liu}
}