Boosting SW Development Efficiency with Function Lifetime Diagrams

Embedded systems play a crucial role in today’s Internet-of-Things (IoT) ecosystems. These systems can range from simple sensors to edge Artificial Intelligence (AI) solutions. However, their complex Hardware (HW)/Software (SW) interactions demand new analytical methodologies which encompass both the HW and the SW execution.In this work, we present a novel approach for early visualization of complex HW/SW interactions during SW development for embedded systems. Our approach traces the lifetime of HW and SW functions during the simulation of a Virtual Prototype (VP), which represents the HW while executing the SW. We dynamically instrument the execution of the VP at runtime such that neither the VP binary file nor the SW binary file has to be modified for tracing. The results are presented as a Function Lifetime Diagram (FLD) by storing the data into the Fast Transaction Recording (FTR) file format, which can be visualized, e.g. by the Surfer waveform viewer.To demonstrate the effectiveness of our approach, we first analyze the HW and SW interactions of a Micro-Electro-Mechanical System (MEMS) sensor. More specifically, the root causes of two already identified HW/SW interaction issues are analyzed. Second, the application flow of an edge AI application for recognizing handwritten digits on a touch display utilizing a pretrained Neural Network (NN) is analyzed. These experiments demonstrate that FLDs provide an effective abstraction to foster a deeper understanding of the embedded system behavior. An additional runtime evaluation reveals an approximately 1.9-fold runtime overhead, demonstrating that our instrumentation approach remains runtime-efficient even for larger IoT applications.