Software defect prediction helps improve software quality and allocate software test resources reasonably. Many defect prediction models based on software metrics have been proposed. However

the existing software metrics are mainly focused on structure information of source code

and the semantic information is lacking. Compilation optimization is the result of deep analysis of program semantics

and intuitively we believe that it should reflect the semantic information of the program in some ways to help defect prediction. Based on the optimization options widely used in the current compiler

this paper extracts 9 compilation optimization metrics

and proposes five types of metrics models that designed by different metrics sets. The relationship between compilation optimization metrics and software defect predictions was evaluated by 13 commonly used classifiers in weka

and also compared with DP-CNN. Experimental results show:Compilation optimization metrics have a significant impact on the recall rate of software defect prediction; Static code metrics combined with compilation optimization metrics can improve the performance of software defect prediction in all classifiers

which can improve the performance of prediction by about 5%; Code size based optimization metrics and performance based optimization metrics have their characteristics

combined both of them can get better performance in software defect prediction.