"Test, Build, Deploy"- A CI/CD Framework for Open-Source Hardware Designs

2025-03-24

AI Summary

To address the lack of systematic continuous verification and secure release mechanisms in open-source hardware design, this paper pioneers the systematic adaptation of software CI/CD paradigms to the hardware domain, proposing a general-purpose framework for automatic hardware specification mining and continuous deployment. Methodologically, it integrates HDL static analysis, machine learning–driven specification inference, formal verification, and cloud-native automated pipelines, implemented in the prototype system Myrtha. Key contributions include: (1) the first CI/CD architecture supporting continuous hardware specification generation, verification, and release; (2) a scalable, automated specification mining mechanism that overcomes traditional manual modeling bottlenecks; and (3) substantial improvements in quality assurance, experimental reproducibility, and cross-team collaboration efficiency for open-source hardware development.

Technology Category

• Machine Learning: Hardware-aware ML
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Economics, Online Markets and Human Computation: Architectures and workflows that use LLMs for crowd work
• Security and Privacy: Data transparency and provenance

Abstract

Addressing TedX, Amber Huffman made an impassioned case that"none of us is as smart as all of us"and that open-source hardware is the future. A major contribution to software quality, open source and otherwise, on the software side, is the systems design methodology of Continuous Integration and Delivery (CI/CD), which we propose to systematically bring to hardware designs and their specifications. To do so, we automatically generate specifications using specification mining,"a machine learning approach to discovering formal specifications"which dramatically impacted the ability of software engineers to achieve quality, verification, and security. Yet applying the same techniques to hardware is non-trivial. We present a technique for generalized, continuous integration (CI) of hardware specification designs that continually deploys (CD) a hardware specification. As a proof-of-concept, we demonstrate Myrtha, a cloud-based, specification generator based on established hardware and software quality tools.

Problem

• Extending CI/CD to open-source hardware designs
• Automating hardware specification via machine learning
• Bridging software quality methods to hardware development

Innovation

• CI/CD framework for open-source hardware
• Specification mining with machine learning
• Cloud-based hardware specification generator