Jbench

Abstract

Race detection is increasingly popular, both in the academic research and in industrial practice. However, there is no specialized and comprehensive dataset of the data race, making it difficult to achieve the purpose of effectively evaluating race detectors or developing efficient race detection algorithms. In this paper, we presented JBench, a dataset with a total number of 985 data races from real-world applications and academic artifacts. We pointed out the locations of data races, provided source code, provided running commands and standardized storage structure. We also analyzed all the data races and classified them from four aspects: variable type, code structure, method span and cause. Furthermore, we discussed usages of the dataset in two scenarios: optimize race detection techniques and extract concurrency patterns.