Automatic Method for Distinguishing Hardware and Software Faults Based on Software Execution Data and Hardware Performance Counters
Jihyun Park, Byoungju Choi
Abstract
Debugging in an embedded system where hardware and software are tightly coupled and have restricted resources is far from trivial. When hardware defects appear as if they were software defects, determining the real source becomes challenging. In this study, we propose an automated method of distinguishing whether a defect originates from the hardware or software at the stage of integration testing of hardware and software. Our method overcomes the limitations of the embedded environment, minimizes the effects on runtime, and identifies defects by obtaining and analyzing software execution data and hardware performance counters. We analyze the effects of the proposed method through an empirical study. The experimental results reveal that our method can effectively distinguish defects.