Simulated annealing and variable neighborhood search algorithm for automated software services composition

The process of software-as-a-service (SaaS) development is critical in developing time as well as in quality aspects. The tools for semiautomatic or even automatic composition of software services are already implemented. However the problem of the quality of the resulting SaaS system still exists. There is huge number of the services-components (subsystems) with the same functionality but different non-functional attributes and relatively short time to evaluate them. In this paper the method for optimal set of services-components selection taking into account non-functional properties of services-components is proposed. This method can be used as an extension of other proofs-as-programs methods and service-oriented software development systems.We have presented the simulated annealing algorithm with variable neighborhood search for automated software composition and have evaluated this algorithm experimentally, comparing it to the Classic SA and Greedy algorithms. The algorithm for the evaluation and improvement of the services-components set we are proposed in this paper presents the class of algorithms because it is possible to change the globality of our optimization algorithm using different values of the parameters.