New applications relying on embedded systems technologies often come with an increased number of features and functionalities. For instance, improved safety, reliability, usability or reduced power consumption are commonly encountered aspects. Those in turn, however, come usually at the cost of increased complexity. Managing the latter can become challenging, especially when looking at (worst-case) execution times or memory usage of embedded systems. In particular, many applications, e.g., safety-critical or real-time applications, require knowledge about the worst-case execution time and stack usage to make a clear statement on important system parameters such as the overall performance or schedulability with regard to critical deadlines. Assessing these properties require elaborate tool support and profound knowledge and skills of the developers. In this paper, an evaluation of static analysis tools and the required steps to integrate these in a existing development environment is presented. The toolchain is either considered to be offline or deployed within a cloud-based integrated development environment. The cloud-approach enables ubiquitous access to the results and a unique visualization across multiple platforms. Additionally, the results are demonstrated along with a small use case.
Quality attribute trade-offs in the embedded systems industry: an exploratory case study