Replication_Package_A Process-Centric Mapping of Non-Technical Debt Instances to ISO/IEC 5338 in AI-enabled Projects

Replication Package for: "A Process-Centric Mapping of Non-Technical Debt Instances to ISO/IEC 5338 in AI-enabled Projects" This repository contains the replication package and supplementary materials for the manuscript titled "A Process-Centric Mapping of Non-Technical Debt Instances to ISO/IEC 5338 in AI-enabled Projects", submitted to the Software Quality Journal. This package provides all the necessary artifacts, guidelines, and analytical scripts required to reproduce the qualitative mapping, LLM-based verification, and quantitative Association Rule Mining (ARM) analyses presented in the study. 📂 Contents of the Repository This replication package includes the following three primary components: 1. The_Artifact_and_Prompts.xlsx This Excel workbook contains the final mapping artifact, the Large Language Model (LLM) False Negative (FN) and False Positive (FP) verification templates used in the study, and the supporting data for the quantitative analyses. It is organized into the following worksheets: Mapping Table: Contains the final mapping artifact. NTD taxonomy: Shows the main NTD categories and their subcategories used in this study. FPV: Contains the specific prompt used for False Positive verification. FNV: Contains the specific prompt used for False Negative verification. Process_abbreviations: Contains the abbreviated and full names of all mapped processes. Treemap_data: Contains the raw data and calculations used to generate the treemaps. Process_frequency: Shows the frequency of each mapped process across all NTD categories. Process_Categories: Shows the categorization of the mapped processes according to the ISO/IEC 5338 lifecycle stages. Coverage_data: Shows the calculations performed to obtain the process coverage matrix. 2. Mapping_Guideline.docx The formal protocol developed and utilized by the researchers to conduct the process-centric mapping. 3. Association_rule_mining.py A Jupyter Notebook containing the Python code used to conduct the association rule mining analysis on the final mapping artifact.