Development of Technique for Healing Data Races based on Software Transactional Memory

Abstract

Data races in multi-threaded programs may occur when multiple accesses on different threads access a shared location without proper synchronization, and one of them is a store. It is difficult to develop data race free programs and to manually fix existing data races in the programs, because they may lead to unpredictable results to the programmer. This paper presents a technique that heals data races using software transactional memory. This technique consists of Transactional Region Specifier, which localizes the incorrect code blocks including shared variables, and Instrumentor, which inserts transactional memory codes to heal data races. We evaluate the accuracy of our healing technique using a set of synthetic programs.