Automotive Software Development Research Articles

Automating Fault Test Cases Generation and Execution for Automotive Safety Validation via NLP and HIL Simulation

The complexity and the criticality of automotive electronic implanted systems are steadily advancing and that is especially the case for automotive software development. ISO 26262 describes requirements for the development process to confirm the safety of such complex systems. Among these requirements, fault injection is a reliable technique to assess the effectiveness of safety mechanisms and verify the correct implementation of the safety requirements. However, the method of injecting the fault in the system under test in many cases is still manual and depends on an expert, requiring a high level of knowledge of the system. In complex systems, it consumes time, is difficult to execute, and takes effort, because the testers limit the fault injection experiments and inject the minimum number of possible test cases. Fault injection enables testers to identify and address potential issues with a system under test before they become actual problems. In the automotive industry, failures can have serious hazards. In these systems, it is essential to ensure that the system can operate safely even in the presence of faults. We propose an approach using natural language processing (NLP) technologies to automatically derive the fault test cases from the functional safety requirements (FSRs) and execute them automatically by hardware-in-the-loop (HIL) in real time according to the black-box concept and the ISO 26262 standard. The approach demonstrates effectiveness in automatically identifying fault injection locations and conditions, simplifying the testing process, and providing a scalable solution for various safety-critical systems.

CAD Support for Security and Robustness Analysis of Safety-critical Automotive Software

Modern vehicles contain a multitude of electronic control units that implement software features controlling most of the operational, entertainment, connectivity, and safety aspects of the vehicle. However, with security requirements often being an afterthought in automotive software development, incorporation of such software features with intra- and inter-vehicular connectivity requirements often opens up new attack surfaces. Demonstrations of such security vulnerabilities in past reports and literature bring in the necessity to formally analyze how secure automotive control systems really are against adversarial attacks. Modern vehicles often incorporate onboard monitoring systems that test the sanctity of data samples communicated among controllers and detect possible attack/noise insertion scenarios. The performance of such monitors against security threats also needs to be verified. In this work, we outline a rigorous methodology for estimating the vulnerability of automotive CPSs. We provide a computer-aided design framework that considers the model-based representation of safety-critical automotive controllers and monitoring systems working in a closed loop with vehicle dynamics and verifies their safety and robustness w.r.t. false data injection attacks. Symbolically exploring all possible combinations of attack points of the input automotive CPS, the proposed framework tries to find out which sensor and/or actuation signal is vulnerable by generating stealthy and successful attacks using a formal method-based counter-example guided abstract refinement process. We also validate the efficacy of the proposed framework using a case study performed in an industry-scale simulator.

Modular Over‐the‐air Software Updates for Safety‐critical Real‐time Systems

ABSTRACTAutomotive software is undergoing a rapid change toward artificial intelligence and towards more and more connectedness with other systems. For both, an incremental design paradigm is desired, where the car's software is frequently updated after production but still can guarantee the highest automotive safety standards. We present a design flow and tool framework enabling a DevOps paradigm for automotive software development. DevOps means that software is developed in a continuous loop of development, deployment, usage in the field, collection of runtime data and feedback to the developers for the next design iteration. The software developers get support in defining, developing, and verifying new software functions based on the data gathered in the field by the previous software generation. The software developers can define contracts describing the time and resource assumptions on the integration environment and guarantees for other dependent software components in the system. These contracts allow a composition of software components and proof obligations to be discharged at design time through virtual integration testing and runtime through continuous monitoring of assumptions and guarantees on the software component's interfaces. An update package, consisting of the software component and its contracts, is then automatically created, transferred over the air, and deployed in the car. Monitors derived from the contracts allow for supervising the system's behavior, detecting failures at runtime, and annotating the situation to be included in a data collection, fueling the next design iteration.

Automatically Learning Formal Models from Autonomous Driving Software

The correctness of autonomous driving software is of utmost importance, as incorrect behavior may have catastrophic consequences. Formal model-based engineering techniques can help guarantee correctness and thereby allow the safe deployment of autonomous vehicles. However, challenges exist for widespread industrial adoption of formal methods. One of these challenges is the model construction problem. Manual construction of formal models is time-consuming, error-prone, and intractable for large systems. Automating model construction would be a big step towards widespread industrial adoption of formal methods for system development, re-engineering, and reverse engineering. This article applies active learning techniques to obtain formal models of an existing (under development) autonomous driving software module implemented in MATLAB. This demonstrates the feasibility of automated learning for automotive industrial use. Additionally, practical challenges in applying automata learning, and possible directions for integrating automata learning into the automotive software development workflow, are discussed.

New Framework for Measurement-based Evaluation of Quality in Automotive Software Development

New Framework for Measurement-based Evaluation of Quality in Automotive Software Development

Leadership approach towards Agile, Waterfall and Iterative implementation of the software development products

The automotive industry is one of the most dynamic markets, gathering around many different sectors from material extractions to robotics and cloud computing. The current research analyses the influences and particularities of leadership and identifies the challenges and advantages of the two principal methodologies in software development projects within the automotive industry, Agile and Waterfall. Some aspects of reducing methodological disadvantages are suggested and presented. The aim is to arrive at a sustainable solution that can ensure the delivery of reliable and flexible software products. The impact of these methodologies on the quality standards and project documentation is analyzed, which is a vital part of automotive software development. By influencing the product development lifecycle, there is an opportunity to develop a structured framework that can be adopted to build software products in a more flexible and agile way.

Intellectual Capital Management Increase in Offshoring

Offshoring is a method for companies from automotive software development industry to have access to a larger pool of talents or to reduce the development costs. In order to have success, the management must be prepared for knowledge transfer process that will be different while compared to training a new employee at the headquarters. Many companies fail when this step is made and instead of reducing the costs, the loss can drag down the business even to the bankruptcy. In this paper, it is presented a solution for a systematic knowhow increase for the new offshore team, applicable to the processes of knowledge transfer. Complex trainings and various methods of solving the orders are not recommended immediately after the offshore branch was opened; rather the foundations must be very clear for every employee. The conclusions of this study are encouraging, supporting the companies in investing in the employee’s development and by increasing gradually the knowledge, the result will be solid and the offshoring can become a big success in the company’s development.

Towards Cloud-supported Automotive Software Development and Test

The development of automotive software has been an evolving process for the last decades. As a result, the paradigm of software development which is independent of the target hardware platform has been adopted in almost all parts of the automotive industry. Deploying software to a hardware platform is now controlled by an enormous parameter set stored in a mapping configuration. This led to the creation of numerous vendor-specific tools for electronic control unit (ECU) development. While this approach simplifies and supports the re-usability of vehicle functions it also increases the complexity as well as the difficulty for integration tests and error localization. In this paper, we present a conceptual platform which allows to establish references between different development and test phase items in a developer-friendly way. It revolves around two self-developed tools supported by an extensive AUTOSAR knowledge base. The system creates inter-connectivity so that it becomes easier to locate the actual origin of a misbehavior or to find a test error manifestation in the actual end system for developers and testers alike.

Enabling consistency in view-based system development — The Vitruvius approach

During the development of large software-intensive systems, developers use several modeling languages and tools to describe a system from different viewpoints. Model-driven and view-based technologies have made it easier to define domain-specific languages and transformations.Nevertheless, using several languages leads to fragmentation of information, to redundancies in the system description, and eventually to inconsistencies. Inconsistencies have negative impacts on the system’s quality and are costly to fix. Often, there is no support for consistency management across multiple languages. Using a single language is no practicable solution either, as it is overly complex to define, use, and evolve such a language. View-based development is a suitable approach to deal with complex systems, and is widely used in other engineering disciplines. Still, we need to cope with the problems of fragmentation and consistency.In this paper, we present the Vitruvius approach for consistency in view-based modeling. We describe the approach by formalizing the notion of consistency, presenting languages for consistency preservation, and defining a model-driven development process. Furthermore, we show how existing models can be integrated. We have evaluated our approach at two case studies from component-based and embedded automotive software development, using our prototypical implementation based on the Eclipse Modeling Framework.

Metrics in automotive software development: A systematic literature review

AbstractSoftware is an integrated part of new features within the automotive sector, car manufacturers, the Hersteller Initiative Software (HIS) consortium defined metrics to determine software quality. Yet, problems with assigning metrics to quality attributes often occur in practice. The specified boundary values lead to discussions between contractors and clients as different standards and metric sets are used. This paper studies metrics used in the automotive sector and the quality attributes they address. The HIS, ISO/IEC 25010:2011, and ISO/IEC 26262:2018 are utilized to draw a big picture illustrating (i) which metrics and boundary values are reported in literature, (ii) how the metrics match the standards, (iii) which quality attributes are addressed, and (iv) how the metrics are supported by tools. Our findings from analyzing 38 papers include a catalog of 112 metrics of which 17 define boundary values and 48 are supported by tools. Most of the metrics are concerned with source code, are generic, and not specifically designed for automotive software development. We conclude that many metrics exist, but a clear definition of the metrics' context, notably regarding the construction of flexible and efficient measurement suites, is missing.

A Case Study on Function Point Method applying on Monte Carlo Simulation in Automotive Software Development

A Case Study on Function Point Method applying on Monte Carlo Simulation in Automotive Software Development

AUTILE Framework: An AUTOSAR Driven Agile Development Methodology to Reduce Automotive Software Defects

This article introduces AUTOSAR Driven Agile Development (AUTILE) Framework as a new methodology to develop automotive software with an aim to reduce the number of defects and their severity. Automotive software, developed in a traditional/legacy way, currently must be rewritten from scratch to support new features or modifications in associated hardware. Disruptive automotive megatrends: connectivity, electrification, and autonomous driving continue to demand new features in a complex software-base. As a result, greater quality issues are faced when more functionality is added to traditional, nonstandardized automotive software. Several researchers have proposed standardization of automotive software to improve the software quality. However, as yet, the industry lacks a de facto standard. At the heart of the AUTILE Framework, we recommend following automotive open system architecture standard as the basis to design modular and open software architecture. To further realize the benefits of modular software architecture designed in the first phase, AUTILE chooses and integrates Agile methodologies as its software development approach. Widespread adoption of Agile methodologies for automotive software development has not occurred and this research highlights the enablers and barriers in this domain. The proposed framework was applied practically to develop automotive software projects, demonstrating that defect reduction can be accomplished using the steps outlined in this new methodology.

Modeling and Verification of A Timing Protection Mechanism in the OSEK/VDX OS using CSP

Abstract The functions of automobiles are becoming increasingly intelligent, which leads to the increasing number of electrical control units for one automobile. Hence, it makes software migration and extension more complicated. In order to avoid these problems, the standard OSEK/VDX has been proposed jointly by a German automotive company consortium and the University of Karlsruhe. This standard provides specifications for the development of automotive software, this standard has become one of the major standards for real-time automotive operating systems (OSs). Since errors in the automotive OS may pose threat to the safety of people in a vehicle, it is necessary to verify the correctness of the OSEK OS which is used by many manufacturers around the world. Formal methods can be adopted to verify the correctness of both software and hardware. Therefore, we propose a formal model of the OSEK OS at the code level and verify three significant properties of the OSEK-based system. In this study, the code-level OSEK OS is verified to ensure compliance with the specifications. An automotive OS always requires that the systemreacts in a timelymanner to external events and performs the computations within the timing constraints. However, there is a possibility that the running time of the tasks exceeds the timing requirements due to the complexity of the tasks. Therefore, by referring to one of the extensions of the OSEK OS, Automotive Open System Architecture (AUTOSAR), we proposed tpOSEK, which is capable of extending the OSEK OS with a timing protection mechanism in AUTOSAR in this study. In our previous study, it was verified that the higher-priority task cannot be preempted by lower-priority tasks. In this paper, after improvement made to the OSEK OS model by adding interrupt service routine models and alarms, and extension of the OSEK OS model with a timing protection model, we have verified that tpOSEK satisfies three significant properties, which include deadlock f ree, complete and no timeout. These properties represent the basic conditions for the systemto run smoothly. If such properties as deadlock f ree and complete are satisfied, it means no deadlock is encountered by this system and all of the tasks can be scheduled completely. Moreover, if the property timeout cannot be satisfied, it means that none of the tasks would miss the deadline. Based on the tpOSEK model, the correct timing protection APIs can be designed at the code level. Thus, by extending the OSEKOSwith theseAPIs,we can update theOSEKOS faster and the need tomodify the dependent applications can be removed. Furthermore, we have constructed formal models for two industrial cases based on tpOSEK OS to demonstrate the soundness of our methods.

How Neural Networks Change Automotive Software Development

How Neural Networks Change Automotive Software Development

Vehicle Computers - Automotive Software Development Rethought

Vehicle Computers - Automotive Software Development Rethought

Model Inspection Tool for Verification of MATLAB Model Guidelines in Automotive Software Development

Model Inspection Tool for Verification of MATLAB Model Guidelines in Automotive Software Development

Automotive Software in Connected and Autonomous Electric Vehicles: A Review

In the last decade, electric vehicles (EVs) have emerged as a sustainable transportation alternative to traditional internal combustion engine (ICE) cars, with automotive software as the key driver behind the advancements. A well-defined information and communication technology (ICT) architecture, comprised of electronics and software, can increase an EV's energy and cost efficiency, safety and comfort. With connected and autonomous electric vehicles (CAEVs) fast becoming a reality, the importance of software in vehicles increases tenfold. This paper serves as an introduction into the field of electromobility and automotive software. It provides an overview of the software and ICT architecture found in CAEVs and identifies future trends and challenges in automotive software development.

Recent Advances and Trends in On-Board Embedded and Networked Automotive Systems

Modern cars consist of a number of complex embedded and networked systems with steadily increasing requirements in terms of processing and communication resources. Novel automotive applications, such as automated driving, rise new needs and novel design challenges that cover a broad range of hardware/software engineering aspects. In this context, this paper provides an overview of the current technological challenges in on-board and networked automotive systems. This paper encompasses both the state-of-the-art design strategies and the upcoming hardware/software solutions for the next generation of automotive systems, with a special focus on embedded and networked technologies. In particular, this paper surveys current solutions and future trends on models and languages for automotive software development, on-board computational platforms, in-car network architectures and communication protocols, and novel design strategies for cybersecurity and functional safety.

Deployment of Effective Testing Methodology in Automotive Software Development

Software development in automotive industry has bestowed greater comforts and conveniences to mankind. A remarkable progress in this field often faces a setback due to minor defects in the software. So there is recurring need for standardization and implementation of testing strategies. But the process of creation of test scripts to check if the software created complies with its specifications and requirements is both time- and resource-consuming. Generating a short but effective test suite usually requires a lot of manual work and expert knowledge. Patronizing research work in this field is the need of the hour. This paper solves the problem by using Model-Based Testing where test harness and evaluation are performed economically through automation. Simulink Design Verifier and Reactis are the tools used to carry out this purpose in Adaptive Front Light System. The resulting outputs obtained from Simulink Design Verifier and Reactis using Model-Based Testing prove that short test suites can be generated for the model where full model coverage can be achieved easily through automation. The outputs of these test cases when compared with the expected outputs confirm that the model developed is working as per the requirements.

The Evaluation Knowledge of Standard Software Asset using The Seven Samurai Framework

The knowledge which is needed on automotive software development, increases significantly according to large-scale, complexity of automotive software. Therefore, it is very difficult for an engineer to understand the whole software development. This paper introduces a way of constructing a meta-model, which visualizes the knowledge of expert engineers, based on The Seven Samurai framework. It can solve issues of system development by considering the seven types of elements which are defined in this framework. And then, its name was defined based on the famous Japanese cinema. Additionally, this paper shows the evaluation results of applying the meta-model to the evaluation of actual standard software assets in the product line, and then the effectiveness of the proposed approach is confirmed based on the results.