Mutation analysis for system of systems policy

Abstract

A System of Systems(SoS) is a set of constituent systems(CS) that have managerial and operational independence.CSs collaborates and follows the order of SoS for solving the problems which cannot be solved with a system, based on the SoS policies.SoS policy is the description which specifies SoS operation to respond environmental changes. Even though SoS is implemented without a fault, SoS can not guarantee the achievement of the goal because SoS runs on non-deterministic environment.It means that SoS may result in different results with same test data.With this reason, it is needed to test the SoS policies. However, testing SoS policy takes high cost because SoS is large-scale and complex system.Even worse, repetitive executions are also needed since the environment of SoS is non-deterministic.In this thesis, we suggest the mutation analysis for SoS policy.By evaluating test data through mutation analysis, we can prioritize test data and reduce the cost for testing.We define the mutation operators for testing general SoS policy, describe the framework of mutation analysis, and applied this approach to test transportation SoS with Simulation of Urban Mobility(SUMO) simulator.The result in case study shows effective test suite which have high mutation score could detect real faults.Also, we describe how efficient the approach is by showing the execution time according to the number of mutants.In addition the cost can be successfully reduced through sampling the mutants, since mutation score in half of sampled mutants intends to converge the mutation score of comprehensive mutants.Based on the case study, proposed approach can distinguish effective test suite within reasonable cost.