Abstract: The C2 style of software architecture is a typical hierarchical style that emphasizes communication between software components through connectors and other rules.Converting existing software systems to the C2 style can effectively enhance the flexibility and scalability of the system.However,existing software systems face issues such as unclear connectors caused by direct component connections,and ambiguous paths during the evolution of the software system.This paper proposes a rule-based clustering method centered around “core classes” to identify connectors.Utilizing an improved multi-objective optimization genetic algorithm,the CodeT5 model is introduced to guide the mutation process,optimizing the C2 style distance,modular quality,and evolutionary cost,thereby searching for the optimal C2 style software architecture.Finally,based on a reflection model,the diffe-rences in software architecture before and after the evolution of the software system are extracted,generating domain files such as PDDL.Combined with a PDDL interpreter,the evolutionary path is generated.Experiments show that the RBCOC method can effectively identify connectors.The CT5NSGA3 algorithm demonstrates promising performance in the architecture search of C2-style systems.Comparative experiments also verify that the CT5NSGA3 algorithm outperforms the traditional NSGA3 algorithm in several indicators.

Key words: Software architecture, C2 style, Genetic algorithm, PDDL, Evolutionary path planning