Ingo Stürmer

Overview of existing safeguarding techniques for automatically generated code

Code generators are increasingly used in an industrial context to translate graphical models into executable code. Since the code is often deployed in safety-related environments, the quality of the code generators is of paramount importance. In this paper, we will present and discuss state-of-the-art techniques for safeguarding automatic code generation applied in model-based development.

Test suite design for code generation tools

In model-based development, executable specifications (models) are used for the design of the software to be developed. New techniques allow the automatic generation of compact code directly from the model via so-called code generators. However, at present, code generators do not possess the same quality characteristics as C or ADA compilers which have been proven in use. The use of test suites, which make it possible to check compilers systematically, is also a promising approach for code generators. This paper describes the design of such a test suite for code generators, and introduces a new testing approach for code generator transformations.

Generating Test Cases for Code Generators by Unfolding Graph Transformation Systems

Code generators are widely used in the development of embedded software to automatically generate executable code from graphical specifications. However, at present, code generators are not as mature as classical compilers and they need to be extensively tested. This paper proposes a technique for systematically deriving suitable test cases for code generators, involving the interaction of chosen sets of rules. This is done by formalising the behaviour of a code generator by means of graph transformation rules and exploiting unfolding-based techniques. Since the representation of code generators in terms of graph grammars typically makes use of rules with negative application conditions, the unfolding approach is extended to deal with this feature.

Checking and Enforcement of Modeling Guidelines with Graph Transformations

In the automotive industry, the model driven development of software for embedded controller units evolves to become the standard paradigm. In this domain, the development is based on executable block diagrams and StateCharts which are provided by the commonly used tool MATLAB Simulink/Stateflow. Huge catalogues with hundreds of modeling guidelines have already been developed to increase the quality of models and ensure the safety and reliability of the generated code. Checking these guidelines and eliminating detected violations manually during audits is a tremendous amount of boring work. In this paper, we show how graph transformations can be used to automate the process of guideline checking and the execution of repair actions. Based on our experiences in an industrial context, we discuss the pros and cons of graph transformations compared to other specification approaches and we finally present a proposal how to combine graph transformations with other modeling paradigms as the most promising approach.

Experiences with model and autocode reviews in model-based software development

Through the introduction of the model-based development, paradigm models became first class citizens in the development of in-vehicle software and are thus also object to strict quality assurance. Just as code reviews are widespread in classical software development, models also have to undergo a stringent review procedure - particularly if they serve as a basis for automatic software implementation by means of model-based code generators. In addition to model reviews, the generated production code (autocode) must be reviewed by performing so-called autocode reviews. This paper presents our procedures for a combined model and autocode reviews and provides examples, lessons learned, as well as significant experimental results drawn from a typical automotive embedded software development project.

Quality Assurance Methods for Model-Based Development: A Survey and Assessment

This paper examines state-of-the-art quality assurance (QA) techniques for model-based software development in the automotive domain. Both the aims and effort required to apply a certain method are discussed for all relevant QA techniques. Since QA techniques can only be used effectively if they are seamlessly integrated within the overall development process and among each other, an appropriate interconnection and order of application is important. Based on our experience from automotive software development projects, we suggest a QA strategy that includes the selection of QA techniques and the sequence of their application.

Ein Testverfahren für optimierende Codegeneratoren

ZusammenfassungDie im Rahmen der Modell-basierten Entwicklung eingebetteter Steuerungs- und Regelungssoftware eingesetzten optimierenden Codegeneratoren müssen einer intensiven Qualitätssicherung unterzogen werden. Dem Einsatz von Testsuiten kommt dabei eine zentrale Rolle zu. Der Beitrag beschreibt den Aufbau einer modularen Testsuite für Codegeneratoren und schlägt einen Testansatz vor, der eine systematische Prüfung der vom Codegenerator angewendeten Optimierungstechniken ermöglicht. AbstractThe optimising code generators employed as part of the model-based development of embedded control software must undergo intensive quality assurance. The use of test suites plays a central role in this process. This article describes the construction of a modular test suite for code generators and proposes a testing approach which makes a systematic test of the optimisations employed by the code generator possible.

MATE: a model analysis and transformation environment for MATLAB simulink

In the automotive industry, the model driven development of software is generally based on the use of the tool MATLAB Simulink. Huge catalogues with hundreds of modeling guidelines have already been developed to increase the quality of models and ensure the safety and reliability of the generated code. In this paper, we present the MATLAB Simulink Analysis and Transformation Environment (MATE), a tool using metamodeling techniques and visual graph transformations to automate the analysis and correction of models according to these guidelines. The MATE approach is illustrated by a typical example, and compared to other classical approaches for model analysis.

Using Model and Code Reviews in Model-based Development of ECU Software

In the automotive industry, the model-based approach is increasingly establishing itself as a standard paradigm for developing control unit software. Just as code reviews are widespread in classical software development as a quality assurance measure, models also have to undergo a stringent review procedure – particularly if they serve as a starting point for automatic implementation by code generators. In addition to these model reviews, the generated production code is reviewed later in the development process by performing auto code reviews. This article will present procedures for and give an account of experiences with model and code reviews which have been adapted to the model-based development process.