Modeling the Temporal Behavior of Complex Embedded Systems - A Reverse Engineering Approach

Software systems embedded in complex products such as cars, telecom systems and industrial robots are typically very large, containing millions of lines of code, and have been developed by hundreds of engineers over many years. We refer to such software systems as complex embedded systems.When maintaining such systems it is difficult to predict how changes may impact the system behavior, due to the complexity. This is especially true for the temporal properties of the system, e.g. response times, since the temporal behavior is dependent on many factors that are not visible in the implementation, such as execution time. The state-of-the-practice is therefore often the trial-and-error approach, i.e. implement and test. However, errors related to the temporal behavior are often hard to find while testing the system and may cause major economic losses if they occur post-release, since they typically result in system failures.This thesis presents a method for predicting these types of errors in an early stage of development. The specific method proposed is called behavior impact analysis, which aims to predict if a specific change to the system may result in errors related to the temporal behavior. The method especially targets complex embedded systems and by using this analysis method in the software development process, the number of errors introduced when maintaining the system can be reduced. This results in an increased productivity in maintenance as well as an improvement in system reliability.This thesis focuses on the construction and validation of the temporal behavior model necessary for performing a behavior impact analysis. The conclusion of the thesis is that a combination of dynamic analysis and reverse engineering is suitable for modeling the temporal behavior of complex embedded systems. Regarding validation of temporal behavior models, the thesis propose a process containing five increasingly demanding tests of model validity. Tools are presented that support the model construction and validation processes.