# Studying, Identifying, and Fixing Hidden Technical Debt in AI-Intensive Cyber-Physical Systems

arXiv: https://arxiv.org/abs/2608.02638 · HTML: https://mlsanity.com/paper/2608.02638/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 6 of its 23 references that are in the map.
- First posted on arXiv 31 Jul 2026.

## Builds on (most cited first, 6 of 6)

- [Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study](https://mlsanity.com/paper/2103.09783/) (2021)
- [Aspirations and Practice of Model Documentation: Moving the Needle with Nudging and Traceability](https://mlsanity.com/paper/2204.06425/) (2022)
- [Automatic Identification of Self-Admitted Technical Debt from Four Different Sources](https://mlsanity.com/paper/2202.02387/) (2022)
- [Towards Automatically Addressing Self-Admitted Technical Debt: How Far Are We?](https://mlsanity.com/paper/2308.08943/) (2023)
- [A Taxonomy of Self-Admitted Technical Debt in Deep Learning Systems](https://mlsanity.com/paper/2409.11826/) (2024)
- [Testing CPS with Design Assumptions-Based Metamorphic Relations and Genetic Programming](https://mlsanity.com/paper/2412.03330/) (2024)

## Abstract (arXiv)

Artificial Intelligence (AI) components are increasingly pervasive in several software systems, including Cyber-Physical Systems (CPSs). AI-CPS are used in several domains, including autonomous vehicles, industry, home automation, robotics, and healthcare. Being composed of hardware, AI components, and conventional modules, AI-CPS can exhibit technical debt (TD) that is peculiar and potentially more challenging than that of conventional systems. This thesis aims to characterize AI-CPS TD and propose approaches for its identification and repair. In a first phase, we characterize AI-CPS TD by analyzing AI ecosystems and AI-CPS repositories, as well as interviewing developers. Based on the acquired knowledge, we define approaches to identify and mitigate such TD. Finally, we plan to develop and validate an automated tool that supports agentic AI solutions to monitor, govern, and repay AI-CPS TD.