When Does the Dependency Graph Help Code-to-Architecture Mapping?
Architectural technical debt arises when a system's implementation drifts from its inten ded modular decomposition, while the mapping between source files and architectural modu les is missing, incomplete, or costly to maintain manually. We formulate code-to-archite cture mapping as semi-supervised node classification over a directed multi-relational de pendency graph, with files as nodes, typed dependencies as edges, and lexical features d erived from code identifiers and directory layout. Starting from a small labeled sample, an iterative self-training procedure expands the mapping to the remaining files. We com pare a graph convolutional network (GCN), a graph attention network (GAT), ...
| Authors | Rakhshanda Jabeen, Morgan Ericsson, Jonas Nordqvist et al. |
|---|---|
| Primary category | cs.SE |
| Published | 14 October 2026 |
| Last updated at source | 14 October 2026 |
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