PaTaS - Quality Assurance in Model-Driven Software Engineering for Spacecraft

Within PATAS (Product Assurance with TASTE Study), a product quality model with software and model metrics is developed and implemented in an end-to-end model-driven software engineering (MDSE) lifecycle demonstrator, based on TASTE. The goal of this study is to find applicable concepts to maintain quality and dependability levels, when MDSE is applied. This requires the definition of connected model and software quality indicators. These indicators are identified and integrated with ESA's reference software product quality model (ECSS-Q-HB-80-04A). The resulting quality model is integrated in a model-based software development lifecycle demonstrator, based on TASTE. To evaluate this demonstrator and the integrated quality indicators, mission-critical parts of the command and data handling subsystem of a satellite mission are modelled and subsequently coded, simulating a realistic development scenario as use case. The aim of the activity is to demonstrate the effect of the end-to-end lifecycle in combination with the developed quality model on the final onboard software product. The final results will set the baseline for recommendations to improve Quality Assurance in MDSE at ESA. In this talk, we present the on-going study and its latest results

PaTaS: Quality Assurance for Model-driven Software Development

The quality of software products in safety critical applications, extensively found within the space domain, is a key success factor but also a major cost driver. To ensure high quality of the software product, quality assurance processes with quality models and metrics are applied. With these tools and processes, product assurance managers and software developers are able to quantify the quality of the software under development. Within the ESA-funded study PaTaS (Product Assurance with TASTE Study), a product quality model with software and model metrics was developed and implemented in an end-to-end model-driven software development (MDSD) life cycle demonstrator. The goal of this study was to identify applicable concepts to maintain quality and dependability levels when MDSD is applied. This requires the definition of connected model and software quality indicators. These indicators were integrated into ESA’s reference software product quality model (ECSS-Q-HB-80-04A). The resulting adapted quality model got incorporated in a model-driven software development life cycle demonstrator. To evaluate this demonstrator and the integrated quality indicators in a realistic development scenario, mission-critical parts of the command and data handling subsystem of a satellite mission were modelled and subsequently coded. The aim of the activity was to demonstrate the effect of the end-to-end life cycle in combination with the developed quality model on the final onboard software product. In this paper we present the result of the study. The focus is on the quality model for MDSD and new quality metrics for models, which can be embedded in an end-to-end model-driven product development life cycle

A Qualitative Investigation of UML Modeling Conventions

Abstract. Modelers tend to exploit the various degrees of freedom provided by the UML. The lack of uniformity and the large amount of defects contained in UML models result in miscommunication between different readers. To prevent these problems we propose modeling conventions, analogue to coding conventions for programming. This work reports on a controlled experiment to explore the effect of modeling conventions on defect density and modeling effort. 106 masters ’ students participated over a six-weeks period. Our results indicate that decreased defect density is attainable at the cost of increased effort when using modeling conventions, and moreover, that this trade-off is increased if tool-support is provided. Additionally we report observations on the subjects ’ adherence to and attitude towards modeling conventions. Our observations indicate that efficient integration of convention support in the modeling process, e.g. through training and seamless tool integration, forms a promising direction towards preventing defects.