E-RACE, A HARDWARE-ASSISTED APPROACH TO LOCKSET-BASED DATA RACE DETECTION ON EMBEDDED PRODUCTS

Lily Huang1,  Michael Smith1,  Albert Tran1,  James Miller2

University of Calgary, Canada1,
University of Alberta, Canada2,

smithmr@ucalgary.ca


Abstract

Limited research exists for identifying data races under the specific characteristics found in embedded systems (e.g. limited memory, stricter timing constraints, etc.). We describe E-RACE, a new style of data-race identification tool which directly utilizes specialized hardware capabilities to monitor the flow of data and instructions. When compared to existing data race analysis approaches, the hardware-assisted E-RACE tool has advantages of recognizing data-race issues without requiring extensive software code instrumentation. The tool was specifically designed to be integrated into an Embedded Unit Testing Driven Development Framework to encourage writing of testable code and early identification of data-races.