Replication package for A Unified Cross-Language Intermediate Representation for Infrastructure-as-Code Smell Detection

General Description: This release includes the four IaC full dataset, the four IaC oracle dataset, the code for IaCIR described in the paper, and the prompt used for the zero-shot LLM evaluation. All the results are described in our paper. All required artifacts are attached to this release. Users can easily access and execute our tool by following the steps listed in the Getting Started section in the README.md file. Users can download the project and run the main.py in the Code folder to test IaCIR on the IaC dataset. Users should read the README.md files in each folder to understand the purpose of each file within the folder. Package Structure: You can check the datasets under the "data" folder. You can check the code for IaCIR under the "code" folder. You can check the complete motivation example in the "figure" folder.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-03-27
DOI
https://doi.org/10.5281/zenodo.19246437
Primary Topic
Adversarial Robustness in Machine Learning
Type
article
Field-Weighted Citation Impact
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article

Replication package for A Unified Cross-Language Intermediate Representation for Infrastructure-as-Code Smell Detection

Anonymous
Zenodo (CERN European Organization for Nuclear Research)
Adversarial Robustness in Machine Learning
article

Replication package for A Unified Cross-Language Intermediate Representation for Infrastructure-as-Code Smell Detection

Anonymous
article en

Abstract

General Description: This release includes the four IaC full dataset, the four IaC oracle dataset, the code for IaCIR described in the paper, and the prompt used for the zero-shot LLM evaluation. All the results are described in our paper. All required artifacts are attached to this release. Users can easily access and execute our tool by following the steps listed in the Getting Started section in the README.md file. Users can download the project and run the main.py in the Code folder to test IaCIR on the IaC dataset. Users should read the README.md files in each folder to understand the purpose of each file within the folder. Package Structure: You can check the datasets under the "data" folder. You can check the code for IaCIR under the "code" folder. You can check the complete motivation example in the "figure" folder.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 5%
Adversarial Robustness in Machine Learning
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