Early timing analysis based on scenario requirements and platform models

Distributed, software-intensive systems (e.g., in the automotive sector) must fulfill communication requirements under hard real-time constraints. The requirements have to be documented and validated carefully using a systematic requirements engineering (RE) approach, for example, by applying scenario-based requirements notations. The resources of the execution platforms and their properties (e.g., CPU frequency or bus throughput) induce effects on the timing behavior, which may lead to violations of the real-time requirements. Nowadays, the platform properties and their induced timing effects are verified against the real-time requirements by means of timing analysis techniques mostly implemented in commercial-off-the-shelf tools. However, such timing analyses are conducted in late development phases since they rely on artifacts produced during these phases (e.g., the platform-specific code). In order to enable early timing analyses already during RE, we extend a scenario-based requirements notation with allocation means to platform models and define operational semantics for the purpose of simulation-based, platform-aware timing analyses. We illustrate and evaluate the approach with an automotive software-intensive system

Migrating from proprietary tools to open-source software for EAST-ADL metamodel generation and evolution

Open-source software has numerous advantages over proprietary commercial-off-The-shelf (COTS) software. However, there are modeling languages, tool chains, and tool frameworks that are developed and maintained in an open-source manner but still incorporate COTS tools. Such an incorporation of COTS tools into an overall open-source approach completely annihilates the actual open-source advantages and goals. In this tool paper, we demonstrate how we eliminated a COTS tool from the otherwise open-source-based generation and evolution workflow of the domain-specific modeling language East-Adl, used in the automotive industry to describe a variety of interdisciplinary aspects of vehicle systems. By switching to a pure open-source solution, East-Adl becomes easier to inspect, evolve, and develop a community around. We compare both the mixed COTS/open-source and the open-source-only workflows, outline the advantages of the open-source-only solution, and show that we achieve equivalent tooling features compared to the original approach

Early Timing Analysis based on Scenario Requirements and Platform Models (Extended Abstract)

This extended abstract summarizes our article [HDF22], published in the Journal of Software and Systems Modeling and presented as Journal First paper at MODELS\u2722

Exploiting Meta-Model Structures in the Generation of Xtext Editors

When generating textual editors for large and highly structured meta-models, it is possible to extend Xtext’s generator capabilities and the default implementations it provides. These extensions provide additional features such as formatters and more precise scoping for cross-references. However, for large metamodels in particular, the realization of such extensions typically is a time-consuming, awkward, and repetitive task. For some of these tasks, we motivate, present, and discuss in this position paper automatic solutions that exploit the structure of the underlying metamodel. Furthermore, we demonstrate how we used them in the development of a textual editor for EATXT, a textual concrete syntax for the automotive architecture description language EAST-ADL. This work in progress contributes to our larger goal of building a language workbench for blended modelling

Creating Python-Style Domain Specific Languages: A Semi-Automated Approach and Intermediate Results

Xtext is a well-known domain-specific language design framework and technology. It automatically generates a textual grammar for a language, given a meta-model specified in Ecore. These generated textual grammars are typically not user-friendly. Python-style languages are popular among developers for their usability and conciseness. We aim to propose a systematic approach to transform a DSL with a generated grammar into a Python-style DSL. To achieve this, we analyze the problems of grammars generated with Xtext, based on a lightweight architecture description language. In response to these problems, we propose a general semi-automated grammar adaptation approach. We apply the approach to two other DSLs to validate the generalization of the approach. We also discuss the limitations of this approach and prospects for the future