SSRD: Shapes and Summaries for Race Detection in Concurrent Data Structures

Explore a novel approach to detecting data races in concurrent dynamic data structures through this 17-minute video presentation from the ISMM 2024 conference. Delve into the SSRD (Shapes and Summaries for Race Detection) technique, which combines concolic testing with summarization-guided exploration of data structure shapes. Learn how this method efficiently identifies and confirms potential data races by generating function summaries that capture pointer-pointee relations and symbolic memory accesses. Discover the advantages of this approach in reducing constraint solving time and improving race detection capabilities compared to existing tools. Gain insights into its application on widely used data structures such as Skip List, Unrolled Linked List, Priority Queue, and AVL Tree. Understand the implications for enhancing the reliability and performance of multithreaded programs relying on concurrent data structures.

[ISMM24] SSRD: Shapes and Summaries for Race Detection in Concurrent Data Structures