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.

This article reports on the experience of monitoring the evolution of a product family of financial Web service software system with OO-metrics over a period of three years. Every four to six months, a snapshot of the system was taken and a set of OO metrics was computed. The classes with extreme metric values or important value changes became the focus of analysis and discussions among the developers, designers, and managers. This way, potential problems were identified and corrected early.

This paper presents a method to view a system as a hierarchy of modules according to information hiding concepts and to identify architectural component candidates in this hierarchy. The result of the method eases the understanding of a system's underlying software architecture. A prototype tool implementing this method was applied to three systems written in C (each over 30 Kloc). For one of these systems, an author of the system created an architectural description. The components generated by our method correspond to those of this architectural description in almost all cases. For the other two systems, most of the components resulting from the method correspond to meaningful system abstractions

This article presents an approach to identify abstract data types (ADT) and abstract state encapsulations (ASE, also called abstract objects) in source code. This approach groups together functions, types, and variables into ADT and ASE candidates according to the proportion of features they share. The set of features considered includes the context of these elements, the relationships to their environment, and informal information. A prototype tool has been implemented to support this approach. It has been applied to three C systems (each between 30-38 Kloc). The ADTs and ASEs identified by the approach are compared to those identified by software engineers who did not know the proposed approach. In a case study, this approach has been shown to identify, in most cases, more ADTs and ASEs than five published techniques applied on the same systems. This is important when trying to identify as many ADTs and ASEs as possible.

The definition and use of multi-valued constant propagation analysis (MVCP), which is an extension of simple constant propagation analysis, is presented in this paper in the context of a user interface reengineering process. A brief description of the adopted COBOL/CICS user interface reengineering model, which makes use of an Abstract User Interface Description Language (AUIDL) to represent user interface structures and behavior, is also given. The experimental context is described and results are shown and discussed. Suggestions for further directions of research and investigation are also presented.

An extension of simple constant propagation analysis is presented in the context of the ongoing Macroscope project on the reengineering of user interfaces. Multi-valued constant propagation analysis (MVCP) is needed to extract user interface behavioral specifications from source code. Structural and behavioral specifications are used to generate new user interface code that will be integrated into the original system. The flow analysis aspects involved in the MVCP approach are described together with an overall view of the user interface reengineering project. The motivations and advantages of such an analysis method are presented.>