Set-Based Concurrent Engineering Model for Automotive Electronic/Software Systems Development

Organised by: Cranfield UniversityThis paper is presenting a proposal of a novel approach to automotive electronic/software systems development. It is based on the combination of Set-Based Concurrent Engineering, a Toyota approach to product development, with the standard V-Model of software development. Automotive industry currently faces the problem of growing complexity of electronic/software systems. This issue is especially visible at the level of integration of these systems which is difficult and error-prone. The presented conceptual proposal is to establish better processes that could handle the electronic/software systems design and development in a more integrated and consistent manner.Mori Seiki – The Machine Tool Compan

Model Checking with Program Slicing Based on Variable Dependence Graphs

In embedded control systems, the potential risks of software defects have been increasing because of software complexity which leads to, for example, timing related problems. These defects are rarely found by tests or simulations. To detect such defects, we propose a modeling method which can generate software models for model checking with a program slicing technique based on a variable dependence graph. We have applied the proposed method to one case in automotive control software and demonstrated the effectiveness of the method. Furthermore, we developed a software tool to automate model generation and achieved a 35% decrease in total verification time on model checking.Comment: In Proceedings FTSCS 2012, arXiv:1212.657

Predicting and Evaluating Software Model Growth in the Automotive Industry

The size of a software artifact influences the software quality and impacts the development process. In industry, when software size exceeds certain thresholds, memory errors accumulate and development tools might not be able to cope anymore, resulting in a lengthy program start up times, failing builds, or memory problems at unpredictable times. Thus, foreseeing critical growth in software modules meets a high demand in industrial practice. Predicting the time when the size grows to the level where maintenance is needed prevents unexpected efforts and helps to spot problematic artifacts before they become critical. Although the amount of prediction approaches in literature is vast, it is unclear how well they fit with prerequisites and expectations from practice. In this paper, we perform an industrial case study at an automotive manufacturer to explore applicability and usability of prediction approaches in practice. In a first step, we collect the most relevant prediction approaches from literature, including both, approaches using statistics and machine learning. Furthermore, we elicit expectations towards predictions from practitioners using a survey and stakeholder workshops. At the same time, we measure software size of 48 software artifacts by mining four years of revision history, resulting in 4,547 data points. In the last step, we assess the applicability of state-of-the-art prediction approaches using the collected data by systematically analyzing how well they fulfill the practitioners' expectations. Our main contribution is a comparison of commonly used prediction approaches in a real world industrial setting while considering stakeholder expectations. We show that the approaches provide significantly different results regarding prediction accuracy and that the statistical approaches fit our data best

A sensitivity analysis on the springback behavior of the Unconstrained Bending Problem

Sheet metal forming software is commonly used in the automotive and sheet metal\ud sectors to support the design stage. However, the ability of the currently available software to\ud accurately predict springback is limited. A sensitivity analysis of the springback behavior of a\ud simple product is performed to gain more knowledge into the various factors contributing to the\ud predictability of springback. The sensitivity analysis comprises both numerical and physical\ud aspects and results are reported in this article

Managed Evolution of Automotive Software Product Line Architectures: A Systematic Literature Study

The rapidly growing number of software-based features in the automotive domain as well as the special requirements in this domain ask for dedicated engineering approaches, models, and processes. Nowadays, software development in the automotive sector is generally developed as product line development, in which major parts of the software are kept adaptable in order to enable reusability of the software in different vehicle variants. In addition, reuse also plays an important role in the development of new vehicle generations in order to reduce development costs. Today, a high number of methods and techniques exist to support the product line driven development of software in the automotive sector. However, these approaches generally consider only partial aspects of development. In this paper, we present an in-depth literature study based on a conceptual model of artifacts and activities for the managed evolution of automotive software product line architectures. We are interested in the coverage of the particular aspects of the conceptual model and, thus, the fields covered in current research and research gaps, respectively. Furthermore, we aim to identify the methods and techniques used to implement automotive software product lines in general, and their usage scope in particular. As a result, this in-depth review reveals that none of the studies represent a holistic approach for the managed evolution of automotive software product lines. In addition, approaches from agile software development are of growing interest in this field

Enabling Multi-Stakeholder Cooperative Modelling in Automotive Software Development and Implications for Model Driven Software Development

One of the motivations for a model driven approach to software development is to increase the involvement for a range of stakeholders in the requirements phases. This inevitably leads to a greater diversity of roles being involved in the production of models, and one of the issues with such diversity is that of providing models which are both accessible and appropriate for the phenomena being modelled. Indeed, such accessibility issues are a clear focus of this workshop. However, a related issue when producing models across multiple parties,often at dierent sites, or even dierent organisations is the management of such model artefacts. In particular, different parties may wish to experiment with model choices. For example, this idea of prototypingprocesses by experimenting with variants of models is one which has been used for many years by business process modellers, in order to highlight the impact of change, and thus improve alignment of process and supporting software specications. The problem often occurs when such variants needed to be merged, for example, to be used within a shared repository. This papers reports upon experiences and ndings of this merging problem as evaluated at Bosch Automotive. At Bosch we have dierent sites where modellers will make changes to shared models, and these models will subsequently require merging into a common repository. Currently, this work has concentrated on one type of diagram, the class diagram. However, it seems clear that the issue of how best to merge models where collaborative multi-party working takes places is one which has a significant potential impact upon the entire model driven process, and, given the diversity of stakeholders, could be particularly problematic for the requirements phase. In fact, class diagrams can also be used for information or data models created in the system analysis step. Hence, we believe that the lessons learned from this work will be valuable in tackling the realities of a commercially viable model driven process

An architecture for enabling A/B experiments in automotive embedded software

A/B experimentation is a known technique for data-driven product development and has demonstrated its value in web-facing businesses. With the digitalisation of the automotive industry, the focus in the industry is shifting towards software. For automotive embedded software to continuously improve, A/B experimentation is considered an important technique. However, the adoption of such a technique is not without challenge. In this paper, we present an architecture to enable A/B testing in automotive embedded software. The design addresses challenges that are unique to the automotive industry in a systematic fashion. Going from hypothesis to practice, our architecture was also applied in practice for running online experiments on a considerable scale. Furthermore, a case study approach was used to compare our proposal with state-of-practice in the automotive industry. We found our architecture design to be relevant and applicable in the efforts of adopting continuous A/B experiments in automotive embedded software.Comment: To appear in the 45th Annual IEEE Conference on Computers, Software and Applications (COMPSAC'2021