Kai-Steffen Jens Hielscher

Stochastic and deterministic performance evaluation of automotive CAN communication

The performance of communication systems can be evaluated using various distinct techniques and paradigms, e.g. queuing theory, simulation or worst case analysis. Mean values for performance measures like transmission delay, queue length or system utilization are valuable information for network dimensioning. However, in many cases, quantile-based approaches or deterministic upper bounds are indispensable, especially for systems that need real-time guarantees. A typical application area are safety-critical functions in automotive environments, where hard real-time transmission deadlines have to be met to assure safe operation of the vehicle. In this paper, we investigate a contemporary automotive in-car communication system, the Controller Area Network (CAN). A simulation study of the system yields stochastic quantile-related use case performance measures for non-time-critical communication. It is complemented by a deterministic evaluation using Network Calculus, which allows to determine worst case transmission times and provides closed and easily applicable formulas for delay bounds of messages on all priority levels. Comprising the outcomes from this dual evaluation approach supports the design, dimensioning and parameterization of the overall CAN bus system with respect to both hard real-time demands and performance characteristics in typical use case scenarios.

Formal specification and systematic model-driven testing of embedded automotive systems

Increasingly intelligent energy-management and safety systems are developed to realize safe and economic automobiles. The realization of these systems is only possible with complex and distributed software. This development poses a challenge for verification and validation. Upcoming standards like ISO 26262 provide requirements for verification and validation during development phases. Advanced test methods are requested for safety critical functions. Formal specification of requirements and appropriate testing strategies in different stages of the development cycle are part of it. In this paper we present our approach to formalize the requirements specification by test models. These models serve as basis for the following testing activities, including the automated derivation of executable test cases from it. Test cases can be derived statistically, randomly on the basis of operational profiles, and deterministically in order to perform different testing strategies. We have applied our approach with a large German OEM in different development stages of active safety and energy management functionalities. The test cases were executed in model-in-the-loop and in hardware-in-the-loop simulation. Errors were identified with our approach both in the requirement specification and in the implementation that were not discovered before.

Model Based Requirements Analysis and Testing of Automotive Systems with Timed Usage Models

In the automotive industry requirements are often still composed of natural language text, spreadsheets, drawings, and formal models. Models are often used to describe partial aspects from the whole set of requirements. Hence, ???aws and vagueness in requirements are common and hard to discover. Upcoming standards like ISO 26262 request the automotive industry to be more strict and formal on the requirements. Formal notation and unambiguitiy is explicitely stated. In the field of system and acceptance testing requirements are the basis for all activities. Although, requirements are often not close to testing. To overcome this we introduced the Timed Usage Model (TUM) as a formal representation of requirements specification. During the creation of the model the requirements are analyzed and brought into an unambiguous and formal representation. Traceability is achieved, as each path in the model must be based upon a requirement. The formulation of the requirements in form of an unambiguous model clarifies the requirements and helps to detect design errors. During the creation of the model omissions and ???aws in the requirements are discovered. The model serves as a communication medium when functionality responsibles are involved to clarify these aspects. Timed Usage Models were created for power train functionality and the energy management. Moreover, the model as a formalized representation of the requirements served as the basis for the whole testing process, including test planning, test case generation, and test campaign analysis.

Introduction of time dependencies in usage model based testing of complex systems

Model-driven testing based on Markov chain usage models (MCUM) is an established method to address testing issues. It is not possible, however, to describe by means of MCUMs the timing of stimuli and time dependencies between inputs and outputs of a system. Additional concepts and information is needed. In this paper it is presented how Timed Usage Models (TUM) can be used to solve this issue. Concepts for stimuli and responses are introduced, that comprise that something must happen before a time interval, after a time interval or within a time interval. It is presented how this can be described by TUMs. TUMs are enhanced MCUMs that allow the usage of distributions of time. The computations for TUMs are based on semi-Markov processes and are therefore not restricted to discrete steps in time. Therefore, indicators and metrics for the test planning and management can be derived that take into account time. Test cases can be derived that reflect variability in inputs and, additionally, variability in timing of inputs. Complex real time systems require a test method that provides the possibility to handle the effect of timing and variability in timing of inputs to the system.

Real-Time Guarantees for CAN Traffic

Modern cars comprise a multitude of electronic features which are implemented in tens of communicating control units. To connect these in-car embedded systems, the CAN bus offers a sustainable performance, hence it is used as a widespread communication infrastructure, even for safety critical applications. However, CAN media access is priority based and performed competitive and non-preemptive. Thus, assessing the worst case end-to-end delay is inevitable in order to provide safe and efficient operation of functions with hard real-time properties. In this paper, we use the analytical method of network calculus to determine guaranteed upper bounds for transmission delays of all CAN priorities. We demonstrate the applicability of our approach by investigating current real-life CAN communication data from the German car manufacturer Audi.

Automated testing of embedded automotive systems from requirement specification models

Embedded software for modern automotive and avionic systems is increasingly complex. In early design phases, even when there is still uncertainty about the feasibility of the requirements, valuable information can be gained from models that describe the expected usage and the desired system reaction. The generation of test cases from these models indicates the feasibility of the intended solution and helps to identify scenarios for which the realization is hardly feasible or the intended system behavior is not properly defined. In this paper we present the formalization of requirements by models to simulate the expected field usage of a system. These so called usage models can be enriched by information about the desired system reaction. Thus, they are the basis for all subsequent testing activities: First, they can be used to verify the first implementation models and design decisions w.r.t. the fulfillment of requirements and second, test cases can be derived in a random or statistic manner. The generation can be controlled with operational profiles that describe different classes of field usage. We have applied our approach at a large German car manufacturer in the early development phase of active safety functionalities. Test cases were generated from the usage models to assess the implementation models in MATLAB/Simulink. The parametrization of the systems could be optimized and a faulty transition in the implementation models was revealed. These design and implementation faults had not been discovered with the established test method.

Modeling and simulation of performance analysis for a cluster-based Web server

Abstract Higher scalability and availability of Web servers are required as the traffic on the Internet has been increasing dramatically over the last few years. This paper focuses on modeling and simulation of the performance analysis for the test system of a cluster-based Web server consisting of five real servers. Three ways of load balancing are introduced, namely, network address translation, IP tunneling and direct routing. Calculation of packet delay is discussed for each part of the running system according to the transferred data in the system. The input model and the system model to measure and simulate the system performance are derived, and the probability distributions of the delay data are specified for using random inputs in the model according to the Q – Q plot and the cumulative distribution function. After the solution of performance tuning problems is evaluated, the maximum process capability of the system is found and a possible performance bottleneck is analyzed.

A Framework for Establishing Performance Guarantees in Industrial Automation Networks

In this paper we investigate the application of Network Calculus for industrial automation networks to obtain performance bounds (latency, jitter and backlog). In our previous work we identified the modeling of industrial networks as the most challenging aspect since in industry most users do not have detailed knowledge about the traffic load caused by applications. However, exactly this knowledge is indispensable when it comes to modeling the corresponding arrival curves. Thus, we suggest the use of generalized traffic profiles, which are provided by the engineering tool. During the engineering process, the user has to specialize these profiles to meet the application configurations. The engineering tool derives the corresponding arrival curves from the specialized profiles and calculates the performance bounds using Network Calculus. To guarantee that the calculated performance bounds are kept during the runtime of the industrial automation, we must ensure that the real traffic flows do not exceed their engineered arrival curves. We therefore propose the use of shapers at the edge of the network domain. The shaper configurations can be automatically derived from the engineered arrival curves of the flows.

Multi-valued Decision Diagrams for the Verification of Consistency in Automotive Product Data

Highly customizable products and mass customization - as increasing trends of the last years - are mainly responsible for an immense growth of complexity within the digital representations of knowledge of car manufacturers. We developed a method to detect and analyze inconsistencies by employing a Multi-Valued Decision Diagram (MDD) which issued to encode the set of all valid product configurations. On this basis, we stated a number of rules of consistency that are checked by a set-based verification scheme.

Modeling and Statistical Testing of Real Time Embedded Automotive Systems by Combination of Test Models and Reference Models in MATLAB/Simulink

Embedded systems become increasingly complex and distributed. Although there is necessity for thourough testing, exhaustive validiation and verification is hardly possible in industry due to time and resource restrictions. In the past the reason for this has often been that it was to time-consuming to specify, to execute, and to evaluate test cases for the first design models and the integrated embedded system. In the meantime methods have become popular in industry that allow the automated generation, execution, and evaluation of test cases. In order to be able to automate these steps all necessary information must be integrated into the models that are the basis for the following steps. The complexity of the system, however, makes the evaluation and assessment of the behavior of the system even more complex. The growth of information needed for this comes along with it. The integration of this information into the model which is used for the generation of test cases is hardly feasible. In this paper we describe how this issue can be addressed by the combination of reference models in MATLAB/Simulink with test models. Time Usage Models (TUM) are employed as test models and provide the basis to generate all possible test scenarios. Model based statistical testing with consideration of time and durations is supported by TUMs. The reference models are used like an executable specification, providing information for the evaluation of the system to be tested. The test model can therefore be kept generic in order to be able to derive virtually any test case from the model, taking account of the potentially infinite sequence of inputs reactive systems might process. We applied the presented approach with a german automotive OEM for the validation and verification of the energy management system.