TY - GEN
T1 - Exploring the Feasibility of ChatGPT for Improving the Quality of Ansible Scripts in Edge-Cloud Infrastructures Through Code Recommendation
AU - Kwon, Sunjae
AU - Lee, Sungu
AU - Kim, Taehyoun
AU - Ryu, Duksan
AU - Baik, Jongmoon
N1 - Publisher Copyright:
© 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2024
Y1 - 2024
N2 - Edge-cloud system aims to reduce the processing time of Big data by bringing massive infrastructures closer to the source of data. Infrastructure as Code (IaC) supports the automatic deployment and management of these infrastructures through reusable code, and Ansible is the most popular IaC tool. As the quality of Ansible script directly influences the quality of Edge-cloud system, many researchers have studied improving the quality of Ansible scripts. However, there has yet to be an attempt to leverage the power of ChatGPT. Thus, we study to explore the feasibility of ChatGPT to improve the quality of Ansible scripts. Three raters evaluate ChatGPT’s code recommendation ability on 48 code revision cases from 25 Ansible project GitHub repositories, and we analyze the rating results. As a result, we can confirm that ChatGPT can recognize and understand Ansible script. However, its ability largely depends on how to user formulates the questions. Thus, we can confirm the need for prompt engineering for ChatGPT to acquire stable code recommendation results.
AB - Edge-cloud system aims to reduce the processing time of Big data by bringing massive infrastructures closer to the source of data. Infrastructure as Code (IaC) supports the automatic deployment and management of these infrastructures through reusable code, and Ansible is the most popular IaC tool. As the quality of Ansible script directly influences the quality of Edge-cloud system, many researchers have studied improving the quality of Ansible scripts. However, there has yet to be an attempt to leverage the power of ChatGPT. Thus, we study to explore the feasibility of ChatGPT to improve the quality of Ansible scripts. Three raters evaluate ChatGPT’s code recommendation ability on 48 code revision cases from 25 Ansible project GitHub repositories, and we analyze the rating results. As a result, we can confirm that ChatGPT can recognize and understand Ansible script. However, its ability largely depends on how to user formulates the questions. Thus, we can confirm the need for prompt engineering for ChatGPT to acquire stable code recommendation results.
KW - Ansible
KW - ChatGPT
KW - Code Recommendation
KW - Edge-cloud
UR - https://www.scopus.com/pages/publications/85181978354
U2 - 10.1007/978-3-031-50385-6_7
DO - 10.1007/978-3-031-50385-6_7
M3 - Conference paper
AN - SCOPUS:85181978354
SN - 9783031503849
T3 - Communications in Computer and Information Science
SP - 75
EP - 83
BT - Current Trends in Web Engineering - ICWE 2023 International Workshops
A2 - Casteleyn, Sven
A2 - Mikkonen, Tommi
A2 - García Simón, Alberto
A2 - Ko, In-Young
A2 - Loseto, Giuseppe
PB - Springer Science and Business Media Deutschland GmbH
T2 - 3rd International Workshop on Big Data Driven Edge Cloud Services, BECS 2023 and 2nd International Workshop on the Semantic Web of Everything, SWEET 2023 and 2nd International Workshop on Web Applications for Life Sciences, WALS 2023, held in conjunction with 23rd International Conference on Web Engineering, ICWE 2023
Y2 - 6 June 2023 through 9 June 2023
ER -