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
- Anonymous
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-03-27
- DOI
- https://doi.org/10.5281/zenodo.19246436
- Primary Topic
- Adversarial Robustness in Machine Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.00