distributed black-box software testing using negative selection

in the software development process, testing is one of the most human intensive steps. many researchers try to automate test case generation to reduce the manual labor of this step. negative selection is a famous algorithm in the field of artificial immune system (ais) and many different applications has been developed using its idea. in this paper we have designed a new algorithm based on negative selection for breeding test cases. our approach, belongs to the category of black-box software testing. moreover, this algorithm can be implemented in a distributed model. two well-known case studies from software testing benchmarks is selected and results show the efficiency of this algorithm