Technical Debt in Data-Intensive Software Systems
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Abstract (arXiv)
The ever-increasing amount, variety as well as generation and processing speed of today's data pose a variety of new challenges for developing Data-Intensive Software Systems (DISS). As with developing other kinds of software systems, developing DISS is often done under severe pressure and strict schedules. Thus, developers of DISS often have to make technical compromises to meet business concerns. This position paper proposes a conceptual model that outlines where Technical Debt (TD) can emerge and proliferate within such data-centric systems by separating a DISS into three parts (Software Systems, Data Storage Systems and Data). Further, the paper illustrates the proliferation of Database Schema Smells as TD items within a relational database-centric software system based on two examples.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). First posted on arXiv 31 May 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 0; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2021Software Engineering for AI-Based Systems: A Surveycited by 69
- 2021Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Studycited by 21
- 2026From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systemscited by 0
- 2026From AI Technical Debt to Agentic Technical Debt: A Systematic Mapping of Root Causes and Manifestations in Agentic AI Systems2 Aug 2026
- 2021Software Engineering for AI-Based Systems: A Survey5 May 2021
- 2021Characterizing Technical Debt and Antipatterns in AI-Based Systems: A Systematic Mapping Study17 Mar 2021