SEMay 5

A Multi-Agent Consensus Protocol for Stable Software Remodularization

arXiv:2605.041885.5
Predicted impact top 100% in SE · last 90 daysOriginality Incremental advance
AI Analysis

Provides a novel approach for software engineers to automatically remodularize code while respecting conflicting quality attributes, though results are preliminary and limited to synthetic and one real-world system.

Reframes software remodularization as a distributed consensus problem among agents, introducing an Asymmetric Monotonic Concession Protocol (AMCP) that negotiates decompositions balancing cohesion and stability. Preliminary experiments show it matches state-of-the-art optimizers under loose stability budgets and enforces strict stability constraints.

Automatic software remodularisation is typically cast as a single-objective optimization problem. While recent metaheuristics have improved search efficiency, real-world architecture recovery must reconcile the conflicting attributes of structural cohesion and evolutionary stability. We reframe software module clustering as a distributed consensus problem among autonomous agents. We introduce an Asymmetric Monotonic Concession Protocol (AMCP) that enables agents to negotiate decompositions that respect multi-attribute utility thresholds. We formally prove the protocol's termination, its bounded concession behaviour consistent with the Zeuthen Strategy under closed-instance conditions, and the local Pareto-satisfactoriness of the resulting partitions. Preliminary experiments on a synthetic benchmark and the Xwork Java framework confirm that our negotiated consensus matches state-of-the-art optimizers when stability budgets are loose, while acting as a "circuit breaker" to enforce strict stability constraints. Extended results on ten further systems, including comparisons with multi-objective evolutionary algorithms and multi-version chains, will be reported in a forthcoming full paper.

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