Towards the self-healing of Infrastructure as Code projects using constrained LLM technologies-Reference-Cited by-同舟云学术

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Towards the self-healing of Infrastructure as Code projects using constrained LLM technologies

Published:2024-04-20 Issue: Volume: Page:22-25
ISSN:
Container-title:Proceedings of the 5th ACM/IEEE International Workshop on Automated Program Repair
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Author:

Diaz-De-Arcaya Josu¹^ORCID,López-De-Armentia Juan¹^ORCID,Zárate Gorka¹^ORCID,Torre-Bastida Ana I.²^ORCID

Affiliation:

1. Tecnalia, Basque Research & Technology Alliance (BRTA), Miñano, Spain

2. Tecnalia, Basque Research & Technology Alliance (BRTA), Derio, Spain

Funder

Basque Government

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3643788.3648014

Reference15 articles.

1. CloudOps: Towards the Operationalization of the Cloud Continuum: Concepts, Challenges and a Reference Framework

2. Yoshua Bengio, Réjean Ducharme, and Pascal Vincent. 2000. A neural probabilistic language model. Advances in neural information processing systems 13 (2000).

3. Thibault Chanus and Michael Aubertin. 2023. LLM and Infrastructure as a Code use case. arXiv preprint arXiv:2309.01456 (2023).

4. Josu Diaz-de Arcaya, Eneko Osaba, Gorka Benguria, Iñaki Etxaniz, Jesus L. Lobo, Juncal Alonso, Ana I Torre-Bastida, and Aitor Almeida. 2023. IEM: A Unified Lifecycle Orchestrator for Multilingual IaC Deployments. In Companion of the 2023 ACM/SPEC International Conference on Performance Engineering. 195--199.

5. Red Hat Inc. 2023. Ansible best practices. https://docs.ansible.com/ansible/2.8/user_guide/playbooks_best_practices.html#best-practices Last accessed 16 November 2023.

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