| Test data generation in program testing is the process of identifying a set of test data that satisfies a selected testing criterion. Branch coverage criterion has been proved to be the best cost-effective in all criterion criteria. But if the number of the branches which has not loop in CFG is more than 10, the number of the feasible and complete paths will be 2~L. It is difficult for testing. This paper introduce Program Block based on the program dependence graph. Partition Method, which eases the testing process. So the testing can be done independently on the program block level. In a Program Block, paths can be generated from dominate tree and implied tree graphs. So the number of the feasible and complete paths can decrease significantly, and the possibility of the complete test is improved.This paper introduce the algorithm of minimum-number-of-paths during using dominate tree and implied tree graphs to generate paths. It generates a path set to cover the unconstrained arcs from the entry to the exit. Then the table of the feasible and complete paths is generated from the Length_N criterion. This paper gives a new GEMGA-based automated approach for path-orientated test data generation. It utilizes GEMGA's prominent feature that can optimize complicated problems without prior knowledge about schema arrangement in chromosomes, and GEMGA explicitly defines the relation,class,and the sample spaces.It precisely defined the relation and class comparison statistics, so that it can improve concurrency level of searching and test coverage. Path problems is important problems during test data generation. This paper offers a solution. The GEMGA-based solution is demenstrated by trials.This paper makes GEMGA-based simulation test, increase the scale of objective test data, and finally improve the coverage possibility. Compared with other simple genetic algorithms, test data is automatically generated by GEMGA with its efficiency, and it can be used to larger applications. |
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