Centralized MLOps Platform for Software Defined Vehicles

Dependency-Aware Over-the-Air Framework for Reliable Software-Defined Vehicle Updates

As the automotive industry transitions toward Software-Defined Vehicle (SDV), Over-the-Air (OTA) updates have become a critical capability. However, conventional update mechanisms often struggle to ensure update success due to the gap between static regulatory compliance and the dynamic operational complexities of modern vehicle architectures. This paper proposes a dependency-aware OTA orchestration framework that addresses these challenges by integrating four operational dimensions—Dependency, Safety, Update Sensitivity, and Governance—into a graph-based scheduling logic. Designed to align with major industrial standards such as AUTOSAR, UNECE R155/R156, and ISO 26262, our framework provides a standardized yet flexible foundation for managing software components across multiple Electronic Control Units (ECUs) environments. Evaluated against a Conventional Sequential Baseline that represents current industrial practices, the proposed approach demonstrates superior performance across three Research Questions (RQs): effectiveness 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. These findings offer actionable insights for implementing high-integrity OTA solutions that meet both functional safety and legal requirements in production-grade SDV environments.

DevOps Beyond Software: Establishing CI/CD Frameworks across Semiconductor and Cloud Engineering Lifecycles

DevOps has changed the way we build and deploy software, focusing on collaboration, automation, continuous integration and continuous delivery (CI/CD). This allows enterprises to provide software faster, with higher quality and greater operational efficiency. While these ideas are frequently employed in traditional software engineering, their use in other technological fields is still limited, despite increasing complexity and increasing demands of speed and dependability. In this post we discuss how CI/CD approaches may be used outside of software development to semiconductor and cloud engineering life-cycles. Disconnected workflows, lengthy validation cycles, varied toolchains and segregated teams can hinder productivity and creativity. Semiconductor creation entails complex procedures of design, simulation, verification and fabrication, while cloud engineering demands constant provisioning of infrastructure, managing configurations, ensuring security and deploying services in ever-changing settings. Such issues point to the necessity for a unified methodology that can integrate automation, traceability and constant feedback across many engineering disciplines. In this work, we propose a comprehensive CI/CD solution, which merges software, semiconductor and cloud engineering processes in one DevOps-driven approach. This framework brings together test automation, versioning, artifact management, infrastructure orchestration, design validation and continuous monitoring into a single scalable engineering environment. This paper presents a realistic case study showing how the implementation 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. The results suggest that the use of DevOps principles in non-traditional domains can yield significant benefits in terms of operational consistency, reduction of human work, and end-to-end visibility along the product life cycle. This study adds to the knowledge of enterprise-wide DevOps adoption by providing a viable roadmap to organizations that aspire to integrate engineering processes, break down domain silos and realize continuous innovation across physical and digital technology ecosystems.

A Fully Automated, Deployment-Aware Testing Pipeline for IoT-Based Automotive Applications

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.

From Timing Budgets to WCETs: Robust SIL-and BSW-Aware Clustering and Allocation for Iterative Automotive Software Development

The SDV Revolution: A New Strategic Framework for Automotive Cockpits

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.

Empirical Evaluation of DevOps Implementation in Optimizing the Software Life Cycle for Cloud Platforms

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