@inproceedings{39f9108a91314598a7ec78d834ffe83f,
title = "Measuring the extent of source code readability using regression analysis",
abstract = "Software maintenance accounts for a large portion of the software life cycle cost. In the software maintenance phase, comprehending the legacy source code is inevitable, which takes most of the time. Source code readability is a metric of the extent of source code comprehension. The better the code is readable, the easier it is for code readers to comprehend the system based on the source code. This paper proposes an enhanced source code readability metric to quantitative measure the extent of code readability, which is more enhanced measurement method than previous research that dichotomously judges whether the source code was readable or not. As an evaluation, we carried out a survey and analyzed them with two-way linear regression analysis to measure the extent of source code readability.",
author = "Sangchul Choi and Suntae Kim and Lee, \{Jeong Hyu\} and Kim, \{Jeong Ah\} and Choi, \{Jae Young\}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; 18th International Conference on Computational Science and Its Applications, ICCSA 2018 ; Conference date: 02-07-2018 Through 05-07-2018",
year = "2018",
doi = "10.1007/978-3-319-95171-3\_32",
language = "English",
isbn = "9783319951706",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "410--421",
editor = "Beniamino Murgante and Apduhan, \{Bernady O.\} and Rocha, \{Ana Maria\} and David Taniar and Eufemia Tarantino and Yeonseung Ryu and Osvaldo Gervasi and Sanjay Misra and Elena Stankova and Torre, \{Carmelo M.\}",
booktitle = "Computational Science and Its Applications – ICCSA 2018 - 18th International Conference, 2018, Proceedings",
}