Functional dependencies and feature interactions are a major source of erroneous and unwanted behavior in software-intensive systems. To overcome these problems, many approaches exist that focus on modeling these functional dependencies in advance, i.e., in the specification or the design of a system. However, there is little empirical data on the amount of such interactions between system functions in realistic systems. In this paper, we analyze structural models of a modern realistic automotive vehicle system with the aim to assess the extent and characteristics of interactions between system functions. Our results show that at least 69% of the analyzed system functions depend on each other or influence each other. These dependencies stretch all over the system whereby single system functions have dependencies to up to 40% of all system functions. These results challenge the current development methods and processes that treat system functions more or less as independent units of functionality.

Model-based development is becoming an increasingly common development methodology. In important domains like embedded systems already major parts of the code are generated from models specified with domain-specific modelling languages. Hence, such models are nowadays an integral part of the software development and maintenance process and therefore have a major economic and strategic value for the software-developing organisations. Nevertheless almost no work has been done on a quality defect that is known to seriously hamper maintenance productivity in classic code-based development: Cloning. This paper presents an approach for the automatic detection of clones in large models as they are used in model-based development of control systems. The approach is based on graph theory and hence can be applied to most graphical data-flow languages. An industrial case study demonstrates the applicability of our approach for the detection of clones in Matlab/Simulink models that are widely used in model-based development of embedded systems in the automotive domain.

Maintainability is a key quality attribute of successful software systems. However, its management in practice is still problematic. Currently, there is no comprehensive basis for assessing and improving the maintainability of software systems. Quality models have been proposed to solve this problem. Nevertheless, existing approaches do not explicitly take into account the maintenance activities, that largely determine the software maintenance effort. This paper proposes a 2-dimensional model of maintainability that explicitly associates system properties with the activities carried out during maintenance. The separation of activities and properties facilitates the identification of sound quality criteria and allows to reason about their interdependencies. This transforms the quality model into a structured and comprehensive quality knowledge base that is usable in industrial project environments. For example, review guidelines can be generated from it. The model is based on an explicit quality metamodel that supports its systematic construction and fosters preciseness as well as completeness. An industrial case study demonstrates the applicability of the model for the evaluation of the maintainability of Matlab Simulink models that are frequently used in model-based development of embedded systems.