Architectural Technical Debt Identification Based on Architecture Decisions and Change Scenarios

Abstract

Architectural technical debt (ATD) is incurred by design decisions that intentionally or unintentionally compromise system-wide quality attributes, particularly maintainability and evolvability. ATD is harmful to the system's long-term health, thus it needs to be identified for further management. However, existing ATD identification approaches are mainly based on source code analysis and thus suffer from certain shortcomings: they can only identify issues at the system implementation, they can only be employed after the systems is implemented in code, they lack a mechanism to confirm whether the potential ATD identified is real ATD or not. To address these issues, we proposed an ATD identification approach based on architecture decisions and change scenarios. To evaluate the effectiveness and usability of this approach, we conducted a case study with an information system in a large telecommunications company. The results show that the proposed approach is useful and easy to use, and it supports release planning and ATD interest measurement.