Automatic software fault localization techniques try to identify the codes obtaining potential faults by comparing the difference on behaviors of correct and false running. Each method has its own adaptive preconditions or environments. Considering these preconditions and environments will be helpful to improve the selection processes and the efficiency of methods. By analyzing the impact of class proportion in test suites on the efficiency of methods deeply, this paper selects ten spectrum-based fault localization methods, including Tarantula, Zoltar and so on, as experimental objects to locate the faults in statement-level existing in programs such as space and flex. Moreover, this paper proposes a metric to evaluate the impact on the efficiency of fault localization with the changing of class proportions in test suites. Experimental results show that the impact of class proportion on the efficiency of methods is multiform. Some methods can keep stable efficiency in a range of balance proportions, but others represent highly sensitivity on the efficiency with the changing of balance proportions.
