Incremental Task-Driven Composition of Heterogeneous Software Models for Legacy System Maintenance

By: Azam Mahdpipour, Vera Pantelic, Sébastien Mosser

Abstract

Maintaining large-scale legacy software systems is complex and time-consuming. Practitioners must integrate diverse artifacts and data, produced by various specialized tools, in order to gain a better understanding of the system and challenges at hand. This process is typically manual and error-prone. In this paper, we propose a solution to support maintenance activities by incrementally merging heterogeneous software models. We build on the existing framework, Unified Data Source (UDS), based on the Single Source of Truth (SST) paradigm. The framework consists of three layers: Probe, SST, and Visualization. The lightweight Probe layer extracts partial models from heterogeneous artifacts and forwards them to the SST layer, which acts as a composition engine that consistently merges the partial models into a unified and coherent representation. The Visualization layer then enables the creation of customized, task-specific model views derived from this unified model. The feasibility and practical value of the method are demonstrated through a systematic, tool-supported approach that applies proven MDE techniques to a concrete system. We showcase this methodology through two real-world use cases: performance troubleshooting and change impact analysis. Both use cases are successfully executed on Spring PetClinic, a widely-used demo project, producing task-specific model views without reconstructing the entire system. These results confirm that task-driven, incremental merging of heterogeneous models is practically achievable, yielding actionable views for practitioners and supporting them in making smarter decisions.

Keywords

Model Driven Reverse Engineering (MDRE), Software Maintenance, Single Source of Truth, Heterogeneous Model Composition, Visualization

Cite as:

Azam Mahdpipour, Vera Pantelic, Sébastien Mosser, “Incremental Task-Driven Composition of Heterogeneous Software Models for Legacy System Maintenance”, Journal of Object Technology, Volume 25, no. 3 ( 2026), pp. 3:141-154, doi:10.5381/jot.2026.25.3.a11.