Constrained Conservative State Symbolic Co-analysis for Ultra-low-power Embedded Systems

Symbolic simulation and symbolic execution techniques have long been used for verifying designs and testing software. Recently, using symbolic hardware-software co-analysis to characterize unused hardware resources across all possible executions of an application running on a processor has been leveraged to enable application-specific analysis and optimization techniques. Like other symbolic simulation techniques, symbolic hardware-software co-analysis does not scale well to complex applications, due to an explosion in the number of execution paths that must be analyzed to characterize all possible executions of an application. To overcome this issue, prior work proposed a scalable approach by maintaining conservative states of the system at previously-visited locations in the application. However, this approach can be too pessimistic in determining the exercisable subset of resources of a hardware design. In this paper, we propose a technique for performing symbolic co-analysis of an application on a processor’s netlist by identifying, propagating, and imposing constraints from the software level onto the gate-level simulation. This produces a more precise, less pessimistic estimate of the gates that an application can exercise when executing on a processor, while guaranteeing coverage of all possible gates that the application can exercise. This also reduces the simulation time of the analysis, significantly, by eliminating the need to explore many simulation paths in the application. Compared to the state-of-art analysis based on conservative states, our constrained approach reduces the number of gates identified as exercisable by up to 34.98%, 11.52% on average, and analysis runtime by up to 84.61%, 43.83% on average.