The Software Engineering (SE) community is prolific, making it challenging for experts to keep up with the flood of new papers and for neophytes to enter the field. Therefore, we posit that the community may benefit from a tool extracting terms and their interrelations from the SE community's text corpus and showing terms' trends. In this paper, we build a prototyping tool using the word embedding technique. We train the embeddings on the SE Body of Knowledge handbook and 15,233 research papers' titles and abstracts. We also create test cases necessary for validation of the training of the embeddings. We provide representative examples showing that the embeddings may aid in summarizing terms and uncovering trends in the knowledge base.
@article{arxiv.2108.09529,
title = {Term Interrelations and Trends in Software Engineering},
author = {Janusan Baskararajah and Lei Zhang and Andriy Miranskyy},
journal= {arXiv preprint arXiv:2108.09529},
year = {2021}
}
Comments
Shortened version appeared in proceedings of ESEC/FSE 2021