Aiming at the problem of large numbers of mutants leading to high mutation testing cost， a Program Dependency based Mutant Generation （PDMG） strategy was proposed to select the mutation implementation objects satisfying certain constraint conditions for mutation generation. Firstly， program dependency graphs were generated based on data dependencies and control dependencies. Then， based on the mutation object selection strategy and program dependency graphs， the dependency statements were selected as mutation objects. Finally， the mutation operator was injected to the selected mutation objects in order to generate mutants. The proposed method was applied to mutation testing of 8 benchmark test programs. Experimental results show that compared with Random Selection （RS） and Mutation Operator Selection （MOS） strategies， PDMG strategy can reduce the mutants by 52.20% on average， improving the execution efficiency of mutation testing without reducing the effectiveness of mutation testing.