2024/05/20 by Dionysios Sklavenitis, Sklavenitis, Dionysios, Dimitris Kalles +1 · 1 citation
Business, Management and Accounting · Decision Sciences · #Auction Theory and Applications #Digital Platforms and Economics #FOS: Computer and information sciences #Software Engineering (cs.SE)
paper · pdf · doi:10.48550/arxiv.2405.11825
openalex publication_date 2024/05/20 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Advances in AI have led to new types of technical debt in software engineering projects. AI-based competition platforms face challenges due to rapid prototyping and a lack of adherence to software engineering principles by participants, resulting in technical debt. Additionally, organizers often lack methods to evaluate platform quality, impacting sustainability and maintainability. In this research, we identify and categorize types of technical debt in AI systems through a scoping review. We develop a questionnaire for assessing technical debt in AI competition platforms, categorizing debt into various types, such as algorithm, architectural, code, configuration, data etc. We introduce Accessibility Debt, specific to AI competition platforms, highlighting challenges participants face due to inadequate platform usability. Our framework for managing technical debt aims to improve the sustainability and effectiveness of these platforms, providing tools for researchers, organizers, and participants.