Optimizing after-sales software maintenance in plugin architecture

Cost optimization is a pressing issue in modern software development and after-sales service. The paper considers optimization of the cost of after-sales service for a plug-in system. The problem of optimal decomposition of functionality is solved under the condition of its delivery in different configurations. A mathematical model is developed that optimizes the distribution of source code files among plug-ins based on the criterion of the minimum cost of after-sales service for the requirements they implement. A software implementation of the model in the Python programming language using the Pyomo module is proposed. A series of computational experiments are performed to solve the optimization problem using various solvers in order to find optimal parameter values and estimate the operating time.