Integration Debt in Multi-Vendor Enterprise Estates: Accumulation Mechanisms and an Assessment Approach
DOI:
https://doi.org/10.71426/jcdt.v1.si1.pp10-18Keywords:
Integration debt, Technical debt, Enterprise integration, Legacy modernization, Software architecture.Abstract
Technical debt is well characterized within application codebases, where it can often be attributed to an owning team and repaid within a single deployment boundary. Integration debt behaves differently. It accumulates between independently governed systems, where release schedules, commercial ownership, platform choices, and semantic definitions are distributed across organizations. This paper treats integration debt as a distinct category and characterizes four accumulation mechanisms in multi-vendor enterprise estates: point-to-point proliferation, semantic divergence, orphaned interfaces, and platform sprawl. We extend the original qualitative assessment with measurable indicators for coupling breadth, specification recoverability, consumer volatility, and semantic divergence, and represent remediation priority as a two-dimensional coordination--knowledge exposure rather than an unsupported scalar debt score. To ground the method in observable interface data, we add a reproducible snapshot of the public APIs.guru OpenAPI directory, whose current metrics expose 3,992 specifications across 677 providers together with validity, reachability, repair, and weekly-change signals. Executable Python code is provided to refresh the snapshot. The resulting framework is intended to sequence remediation: opaque and semantically divergent dependencies are addressed before high-volume but well-understood interfaces, because knowledge loss, unlike coordination cost, can make later modernization effectively unbounded.
References
[1] Alves NSR, Mendes TS, de Mendonça MG, Spínola RO, Shull F, Seaman C. Identification and management of technical debt: A systematic mapping study. Information and Software Technology. 2016;70:100-121. Available from: https://doi.org/10.1016/j.infsof.2015.10.008
[2] Besker T, Martini A, Bosch J. Managing architectural technical debt: A unified model and systematic literature review. Journal of Systems and Software. 2018;135:1-16. Available from: https://doi.org/10.1016/j.jss.2017.09.025
[3] Verdecchia R, Malavolta I, Lago P. Architectural technical debt identification: The research landscape. In: Proceedings of the 2018 International Conference on Technical Debt. 2018. p. 11-20. Available from: https://doi.org/10.1145/3194164.3194176
[4] Martini A, Bosch J, Chaudron M. Investigating architectural technical debt accumulation and refactoring over time: A multiple-case study. Information and Software Technology. 2015;67:237-253. Available from: https://doi.org/10.1016/j.infsof.2015.07.005
[5] Li Z, Avgeriou P, Liang P. A systematic mapping study on technical debt and its management. Journal of Systems and Software. 2015;101:193-220. Available from: https://doi.org/10.1016/j.jss.2014.12.027
[6] Tang X, Sun S, Yuan X, Chen D. Automated web service composition system on enterprise service bus. In: 2009 Third IEEE International Conference on Secure Software Integration and Reliability Improvement. 2009. p. 9-13. Available from: https://doi.org/10.1109/SSIRI.2009.24
[7] Galster M, Lapre L, Avgeriou P. SOA in variability-intensive environments: Pitfalls and best practices. IEEE Software. 2014;31(1):77-84. Available from: https://doi.org/10.1109/MS.2013.21
[8] Kim JS, Andrade H, Sussman A. Principles for designing data-/compute-intensive distributed applications and middleware systems for heterogeneous environments. Journal of Parallel and Distributed Computing. 2007;67(7):755-771. Available from: https://doi.org/10.1016/j.jpdc.2007.04.006
[9] Velepucha V, Flores P. A survey on microservices architecture: Principles, patterns and migration challenges. IEEE Access. 2023;11:88339-88358. Available from: https://doi.org/10.1109/ACCESS.2023.3305687
[10] Soldani J, Tamburri DA, Van Den Heuvel WJ. The pains and gains of microservices: A systematic grey literature review. Journal of Systems and Software. 2018;146:215-232. Available from: https://doi.org/10.1016/j.jss.2018.09.082
[11] Kleehaus M, Matthes F. Challenges in documenting microservice-based IT landscape: A survey from an enterprise architecture management perspective. In: 2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC). 2019. p. 11-20. Available from: https://doi.org/10.1109/EDOC.2019.00012
[12] Alonso J, Orue-Echevarria L, Casola V, Torre AI, Huarte M, Osaba E, Lobo JL. Understanding the challenges and novel architectural models of multi-cloud native applications: A systematic literature review. Journal of Cloud Computing. 2023;12:6. Available from: https://doi.org/10.1186/s13677-022-00367-6
[13] Akidau T, Bradshaw R, Chambers C, Chernyak S, Fernández-Moctezuma RJ, Lax R, McVeety S, Mills D, Perry F, Schmidt E, Whittle S. The Dataflow Model: A practical approach to balancing correctness, latency, and cost in massive-scale, unbounded, out-of-order data processing. Proceedings of the VLDB Endowment. 2015;8(12):1792-1803. Available from: https://doi.org/10.14778/2824032.2824076
[14] Overeem M, Mathijssen M, Jansen S. API-m-FAMM: A focus area maturity model for API management. Information and Software Technology. 2022;147:106890. Available from: https://doi.org/10.1016/j.infsof.2022.106890
[15] Hyrynsalmi SM. The state-of-the-art of the integration platforms as a service research. In: 2022 IEEE/ACM International Workshop on Software-Intensive Business (IWSiB). 2022. p. 17-22. Available from: https://doi.org/10.1145/3524614.3528634
[16] Rahm E, Bernstein PA. A survey of approaches to automatic schema matching. The VLDB Journal. 2001;10(4):334-350. Available from: https://doi.org/10.1007/s007780100057
[17] Wang RY, Strong DM. Beyond accuracy: What data quality means to data consumers. Journal of Management Information Systems. 1996;12(4):5-33. Available from: https://doi.org/10.1080/07421222.1996.11518099
[18] Kruchten P, Nord RL, Ozkaya I. Technical debt: From metaphor to theory and practice. IEEE Software. 2012;29(6):18-21. Available from: https://doi.org/10.1109/MS.2012.167
[19] Ampatzoglou A, Mittas N, Tsintzira AA, Ampatzoglou A, Arvanitou EM, Chatzigeorgiou A, Avgeriou P, Angelis L. Exploring the relation between technical debt principal and interest: An empirical approach. Information and Software Technology. 2020;128:106391. Available from: https://doi.org/10.1016/j.infsof.2020.106391
[20] Lenarduzzi V, Besker T, Taibi D, Martini A, Arcelli Fontana F. A systematic literature review on technical debt prioritization: Strategies, processes, factors, and tools. Journal of Systems and Software. 2021;171:110827. Available from: https://doi.org/10.1016/j.jss.2020.110827
[21] Espinha T, Zaidman A, Gross HG. Web API growing pains: Loosely coupled yet strongly tied. Journal of Systems and Software. 2015;100:27-43. Available from: https://doi.org/10.1016/j.jss.2014.10.014
[22] Koçi R, Franch X, Jovanovic P, Abelló A. Web API evolution patterns: A usage-driven approach. Journal of Systems and Software. 2023;198:111609. Available from: https://doi.org/10.1016/j.jss.2023.111609
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Rajendra Pallikonda (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors retain copyright in their published work subject to the journal's publication and licensing arrangements.
Articles published in JMT are distributed under the Creative Commons Attribution–NonCommercial 4.0 International License (CC BY-NC 4.0).
Under this license, readers may share and adapt published material for non-commercial purposes, provided that:
- Appropriate credit is given to the author or authors.
- The original publication source is acknowledged.
- A link to the applicable license is provided.
- Any modifications are clearly indicated.
Commercial reuse is not permitted under CC BY-NC 4.0 without appropriate authorization from the relevant rights holder.
License details are available at:
Creative Commons Attribution–NonCommercial 4.0 International
DOI prefix: 10.71426
