Extracting Simulation Models from Complex Embedded Real-Time Systems

A modeling process is presented for extracting timing-accurate simulation models from complex embedded real-time systems. The process is supported by two complementary methods for tool-supported model extraction, Model Synthesis and Hybrid Model Extraction. The generated models enable impact analysis for complex real-time systems with respect to dynamic system properties, such as timing and resource usage. This can make software mainetnance more predictable with respect to time-to-market and development costs, since timing errors can be identified early and avoided. The contribution of the paper is the modeling process, the Hybrid Model Extraction method and an interactive modeling tool, MASS, designed to support Hybrid Model Extraction of large implementations in C.

1 Introduction

Managing the evolution of software systems is important in order to preserve the large investments associated with the software. Complex embedded software systems, such as industrial control systems or automotive systems, often consists of several million lines of code and are maintained over many years, sometimes decades, during which the software is exposed for changes continuously. Due to the many changes made over the years, the software systems become larger and more complex. As a consequence, the perspicuity of the system decreases, i.e., it becomes increasingly harder to predict how a change, e.g. a new feature, will impact the behavior of the system. Thereby, it becomes harder to maintain the software, which reflects in development cost and time-to-market. For embedded software systems, which often are multitasking real time systems, an impact analysis is especially difficult as a change's impact on the system's temporal behavior may cause timing errors.