Advancing Technical Debt Management in Software Systems with a Comprehensive TD Indicator and Question Catalog

Author:

Çağlayan Dilek1,Özcan-Top Özden2

Affiliation:

1. ASELSAN A.Ş. & Information Systems Dept., Graduate School of Informatics, Middle East Technical University, Ankara, Türkiye

2. Information Systems Dept., Graduate School of Informatics, Middle East Technical University, Ankara, Türkiye

Abstract

The Technical Debt (TD) metaphor was introduced over three decades ago and continues to challenge software development projects. Despite its recognized importance, there is a lack of comprehensive catalog that not only lists TD types and indicators but also elucidates them. This paper significantly extends our previous work by presenting a detailed catalog of TD types and indicators, enriched with specific assessment questions and in-depth explanations for each indicator. We had extracted and refined TD categories from both academic and gray literature to assemble a list of 120 TD indicators across 10 distinct TD types. For each indicator, we provide detailed description and at least two tailored assessment questions in this version, to aid in the practical evaluation of technical debt. This enhanced catalog is designed to advance the specification and management of technical debt in software development, offering practitioners clear, actionable insights for assessing and addressing TD.

Publisher

Association for Computing Machinery (ACM)

Reference22 articles.

1. 1998. IEEE 830-19T98 Recommended Practice for Software Requirements Specifications Standards.

2. Identification and management of technical debt: A systematic mapping study

3. Nicolli S. R. Alves, Leilane F. Ribeiro, Vivyane Caires, Thiago S. Mendes, and Rodrigo O. Spínola. 2014. Towards an Ontology of Terms on Technical Debt. In Proceedings of the 2014 Sixth International Workshop on Managing Technical Debt (MTD '14). IEEE Computer Society, 1--7.

4. Analyzing the concept of technical debt in the context of agile software development: A systematic literature review

5. Dilek Caglayan and Özden Özcan Top. 2024. Revisiting Technical Debt Types and Indicators for Software Systems. Association for Computing Machinery, 834--841.

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