Technical and Non-Technical Debt Across ISO/IEC 5338 Lifecycle Processes: A Joint Analysis in AI-Integrated Projects

Replication package for “Technical and Non-Technical Debt Across ISO/IEC 5338 Lifecycle Processes: A Joint Analysis in AI-Integrated Projects” This package contains the data, mapping rules, prompts and analysis code of the study. The study maps technical debt (TD) instances from industrial AI-integrated projects to the lifecycle processes of ISO/IEC 5338:2023, ISO/IEC/IEEE 12207:2017 and ISO/IEC/IEEE 15288, and to the process areas of the People Capability Maturity Model (People CMM). It then analyzes 14 technical and non-technical debt categories jointly, using a subset multiple correspondence analysis (MCA) at instance level and a Jaccard similarity network at project level. Files The_Mapping_Tables_and_Prompts.xlsx: the mapping tables and all supporting material, in eight sheets: ReadMe: description of the workbook and of all attributes of the mapping tables. TD Taxonomy: the 14 main debt categories (six non-technical, eight technical) and their subcategories. NTD_Mapping: mapping of the instances of the six non-technical debt categories to ISO processes and People CMM process areas. TD_Mapping: mapping of the instances of the eight technical debt categories to ISO processes. FPV: prompt template for the LLM-assisted false positive verification. FNV: prompt template for the LLM-assisted false negative verification. Process_abbreviations: abbreviations of the process names used in the tables and figures. Interview_demographics: characteristics of the participants, projects and companies. Mapping_Guideline.docx: the rules used to identify candidate processes, assess their relevance to a TD instance, and document the justification of each mapping decision. Interview_guide.pdf: the semi-structured interview guide used to collect the dataset (English translation). Subset_MCA.ipynb: implementation of the subset MCA with project weights (RQ2a), including the leave-one-project-out stability analysis (RV coefficients), the contributions and coordinates of all points, and the MCA maps. Jaccard_implementation.ipynb: implementation of the project-level Jaccard similarity network (RQ2b), including the exclusion rules and the network visualization. Reproducing the analyses The notebooks were developed in Google Colab with Python 3. They read the mapping tables (sheets NTD_Mapping and TD_Mapping) as input; set the file paths in the first cell of each notebook to the location of the workbook or of the exported sheets. Running all cells reproduces the results and figures of RQ2a and RQ2b reported in the paper. Notes Anonymization: names of participants, companies and projects were removed. Projects are identified by codes, and the projects of one participant are merged into one project unit (e.g., P10.1–P10.3 into P10). Copyright: the columns of the mapping tables that quoted text from the ISO/IEC standards and the People CMM (process purposes, activities and tasks, and details) were removed for copyright reasons. Each mapping refers to the relevant clause, so readers with access to the standards can look up the text. Language: the interviews were conducted in Turkish; the case descriptions, root causes and the interview guide were translated into English. LLM use: GPT-4o mini supported the verification of the mapping; every LLM output was reviewed by a researcher before any change was made to the mapping.