AUTOSAR Standard

Staron, Miroslaw; Durisic, Darko

doi:10.1007/978-3-319-58610-6_4

Cited by 12 publications

(3 citation statements)

References 18 publications

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“…This way, we can model and verify all modules independently first (e.g., the kernel body), and only later verify their interaction (e.g., with the context switch model presented here). Early experiences with AUTOSAR [70] have shown that other low-level functionality of the OS, such as device drivers, can also be modeled and verified similarly to the context switch presented here. The individually verified model modules would then be combined for the verification of overarching aspects in complete software stacks.…”

Section: Discussionmentioning

confidence: 73%

A framework for embedded software portability and verification: from formal models to low-level code

Martins Gomes,

Aichernig,

Baunach

2024

Softw Syst Model

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Porting software to new target architectures is a common challenge, particularly when dealing with low-level functionality in drivers or OS kernels that interact directly with hardware. Traditionally, adapting code for different hardware platforms has been a manual and error-prone process. However, with the growing demand for dependability and the increasing hardware diversity in systems like the IoT, new software development approaches are essential. This includes rigorous methods for verifying and automatically porting Real-Time Operating Systems (RTOS) to various devices. Our framework addresses this challenge through formal methods and code generation for embedded RTOS. We demonstrate a hardware-specific part of a kernel model in Event-B, ensuring correctness according to the specification. Since hardware details are only added in late modeling stages, we can reuse most of the model and proofs for multiple targets. In a proof of concept, we refine the generic model for two different architectures, also ensuring safety and liveness properties. We then showcase automatic low-level code generation from the model. Finally, a hardware-independent factorial function model illustrates more potential of our approach.

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Section: Discussionmentioning

confidence: 73%

A framework for embedded software portability and verification: from formal models to low-level code

Martins Gomes,

Aichernig,

Baunach

2024

Softw Syst Model

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“…It focuses on preparation, configuration, instantiation and execution of distributed cosimulations. However, ProMECoS is not to be mistaken for an architecture model, like the Reference Architecture Model Automotive (RAMA) [27] or the Automotive Open System Architecture (AUTOSAR) [28]. It does not reference specific system components, functions, or simulation use cases.…”

Section: Process Model For Efficient Distributed Co-simulation (Promementioning

confidence: 99%

ProMECoS: A Process Model for Efficient Standard-Driven Distributed Co-Simulation

2021

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Co-simulation techniques have evolved significantly over the last 10 years. System simulation and hardware-in-the-loop testing are used to develop innovative products in many industrial sectors. Despite the success of these simulation techniques, their efficient application requires a systematic approach. In practice the integration and coupling of heterogeneous systems still require enormous efforts. At this point in time no unified process for integration and simulation of DCP-based co-simulation scenarios is available. In this article we present ProMECoS, a process model for efficient, standard-driven distributed co-simulation. It defines the necessary tasks required to prepare, instantiate and execute distributed co-simulations according to the DCP standard. Furthermore, it enables the exploitation of front-loading benefits, thus reducing the overall system development effort. ProMECoS is based on the IEEE 1730 standard for Distributed Simulation Engineering and Execution Process. It adopts the artefacts of the DCP specification, and defines additional process artefacts. The DCP specification and its associated default integration methodology were developed by a balanced consortium in context of the ITEA 3 project ACOSAR. The DCP is compatible to the well-adopted FMI standard. Therefore both standards can be used together for seamless development using models, software, and real components. ProMECoS provides the necessary guidance for efficient product development and testing.

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“…1.3 can be found in a number of other application fields, including automotive, avionics, and medical devices, just to name a few. AUTOSAR Classic platform for instance [Staron and Durisic, 2017], which is a standard framework and middleware for developing software for Electronic Control Units (ECU) in cars, is designed to support diverse ECU architectures, ranging from compact low-cost controllers for monitoring tire pressure to high-performance and safety-critical systems for complex powertrain functions [Nilsson et al, 2008]. Although this middleware has a complex architecture that includes layers (i.e.…”

Section: Industrial Safety Controllersmentioning

confidence: 99%

A Compiler and Language Support for Designing Mixed-Criticality Applications

Kajtazovic¹,

Hödl²,

Botler³

2021

jucs

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Coexistence of software components and functions of different criticality in a single computing platform has challenged the safety community for the past two decades. Despite efforts that have been made so far, dealing with mixed-criticality has still left some room for improvements. One particular concern here is that partitioning of hardware and software resources with regard to criticality (safety related, non-safety related) has direct implications on how safety measures need to be realised. For example, a self-test that must meet certain diagnostic coverage for the microcontroller core by inspecting its instructions, needs to cover only those instructions which are able to affect a safety function. Available software mechanisms and tools are to a certain extent still unable to deal with such a fine-grained selection of resources. In this work, we introduce a compiler extension and language support which enable accurate selection of data based on their criticality. The compiler extension serves to establish detailed traceability between the software code and its representation in runtime memory. With the language support, the individual data elements can be classified based on the desired safety integrity level. As a result, safety measures that operate on data (e.g. Abraham test for SRAM can achieve better coverage. The method has been evaluated and applied to industrial safety controllers. We provide here relevant performance figures and discuss possible applications of the method in other fields.

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AUTOSAR Standard

Cited by 12 publications

References 18 publications

A framework for embedded software portability and verification: from formal models to low-level code

A framework for embedded software portability and verification: from formal models to low-level code

ProMECoS: A Process Model for Efficient Standard-Driven Distributed Co-Simulation

A Compiler and Language Support for Designing Mixed-Criticality Applications

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