Jun 2026· 2026 IEEE Cloud Summit· pp. 110-115· 0 citations· 3 references
Abstract
Software complexity in automotive has increased fourfold since 2010, yet productivity has remained flat. This growing gap threatens automakers’ ability to innovate while spending on automotive software continues to climb, over $100billion in recent years, with projections to double every 7 to 8 years. The shift to software defined Vehicles addresses this through hardware consolidation replacing dozens of distributed ECUs with centralized computers that enable software virtualization and hardware to software decoupling. This transformation brings new challenges such as managing ML models across fragmented paltforms, diverse hardware configuration, limited edge computing resources, intermittent connectivity, and strict safety requirements under ISO 26262 and SOTIF. Traditional MLOps practices don’t work in automotive contexts. This paper presents a centralized MLOps platform designed specifically for software defined vehicles, handling the complete ML lifecycle from development to deployment, monitoring and continuous improvement. The platform uses containerization, model versioning, automated validation, edge optimized inference to manage complexity while at the same time delivering the operational excellence required by Software Defined Vehicles.
A dependency-aware OTA orchestration framework that addresses challenges in improving update success rates, efficiency in execution time and update requests through optimized scheduling, and feasibility in maintaining system-wide integrity by successfully reconciling stringent safety requirements and diverse update sensitivity constraints is proposed.
Juyeon Park, In-Young Ko· SIGSOFT FSE Companion· 0 citations
This paper presents a realistic case study showing how the implementation of DevOps principles in cross-functional teams, with the help of the standardized pipelines and integrated automation, facilitates cooperation, reduces cycle times, enhances quality assurance and accelerates delivery outcomes.
Karthik Allam· International Journal of Eme...· 0 citations
This work presents an end-to-end, deployment-aware testing pipeline for IoT-based automotive applications that combines requirement-driven test and code generation with large language model (LLM) and vision-language model (VLM) assistance, and human-in-the-loop curation to reduce manual effort and improve consistency.
Denesa Zyberaj, Roman Vintonyak, Pascal Hirmer et al.· 0 citations
A chain-based analysis model is presented that treats SIL constraints and BSW costs as first-class citizens, as well as an integrated toolchain that constructs job-level data-age constraints, forms SIL-compliant clusters, synthesizes multirate tasks, and maps application and BSW tasks to heterogeneous multicore platforms while checking timing and memory feasibility.
Tobias Denzinger, Matthias Becker, Peter Ulbrich· 1 citation
The transition toward Software-Defined Vehicles (SDVs) is fundamentally reshaping the automotive display and Human-Machine Interface (HMI) landscape. Driven by the deep integration of Artificial Intelligence (AI), the evolution of electronic architectures, and escalating geopolitical tensions, the traditional “larger is better” display paradigm has reached its physical and functional limits. This paper proposes a novel strategic framework, “The Cockpit Decision Reset,” focusing on three critical pillars: supply chain resilience (Just-in-Case), design value prioritization, and HMI logic transformation. We analyze how these factors individually and collectively impact automotive cockpit strategies, shifting the industry from passive screens to proactive, AI-driven environments. Furthermore, this study provides quantitative market forecasts for emerging display technologies, projecting FALD/Mini LED LCD to reach 22.5 million units by 2030, and OLED to reach 11.8 million units by 2030. Concurrently, Micro LED is forecasted to emerge in 2028 with 1.0 K units, growing to 53.0 K units by 2030. New design features such as Panoramic Head-Up Displays (PHUD), Under-Display Cameras (UDC), and Smart Surfaces and Privacy Displays, are also evaluated as essential components of the next-generation cockpit. The proposed framework offers a comprehensive guide for OEMs and Tier 1 suppliers navigating the complex SDV ecosystem.
S. Wu· International Workshop on Ac...· 0 citations
Today, IT organizations, in particular, have to provide quick, reliable and high-quality software solutions for meeting
the changing market requirements. While the development process has been structured by traditional software engineering
paradigms (Waterfall, Agile and Spiral Models), traditional workflows often involve operational bottlenecks. In particular, the
lack of communication and coordination between development and operations can lead to delivery delays. DevOps has come
about as a transformative approach that fuses software design and IT operations into a single, streamlined and automated
process that aims to overcome these systemic inefficiencies. DevOps is used to streamline the software delivery pipeline, when
paired with Cloud Computing infrastructure, including SaaS, PaaS, and IaaS solutions from AWS, Azure, and GCP. In this
project, one will be working on building a Continuous Integration and Continuous Deployment (CI/CD) pipeline using
Microsoft Azure to automate software delivery and improve overall efficiency
Ashwani Kumar, Geetanjali Amarawat· International Journal for Re...· 0 citations