Towards Readability-Aware Recommendations of Source Code Snippets

Athanasios Michailoudis, Themistoklis Diamantopoulos, Andreas Symeonidis

2023

Abstract

Nowadays developers search online for reusable solutions to their problems in the form of source code snippets. As this paradigm can greatly reduce the time and effort required for software development, several systems have been proposed to automate the process of finding reusable snippets. However, contemporary systems also have certain limitations; several of them do not support queries in natural language and/or they only output API calls, thus limiting their ease of use. Moreover, the retrieved snippets are often not grouped according to the APIs/libraries used, while they are only assessed for their functionality, disregarding their readability. In this work, we design a snippet mining methodology that receives queries in natural language and retrieves snippets, which are assessed not only for their functionality but also for their readability. The snippets are grouped according to their used API calls (libraries), thus enabling the developer to determine which solution is best fitted for his/her own source code, and making sure that it will be easily integrated and maintained. Upon providing a preliminary evaluation of our methodology on a set of different programming queries, we conclude that it can be effective in providing reusable and readable source code snippets.

Paper Citation

in Harvard Style

Michailoudis A., Diamantopoulos T. and Symeonidis A. (2023). Towards Readability-Aware Recommendations of Source Code Snippets. In Proceedings of the 18th International Conference on Software Technologies - Volume 1: ICSOFT; ISBN 978-989-758-665-1, SciTePress, pages 688-695. DOI: 10.5220/0012145500003538

in Bibtex Style

@conference{icsoft23,
author={Athanasios Michailoudis and Themistoklis Diamantopoulos and Andreas Symeonidis},
title={Towards Readability-Aware Recommendations of Source Code Snippets},
booktitle={Proceedings of the 18th International Conference on Software Technologies - Volume 1: ICSOFT},
year={2023},
pages={688-695},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012145500003538},
isbn={978-989-758-665-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Conference on Software Technologies - Volume 1: ICSOFT
TI - Towards Readability-Aware Recommendations of Source Code Snippets
SN - 978-989-758-665-1
AU - Michailoudis A.
AU - Diamantopoulos T.
AU - Symeonidis A.
PY - 2023
SP - 688
EP - 695
DO - 10.5220/0012145500003538
PB - SciTePress