Towards Automated Governance: A DSL for Human-Agent Collaboration in Software Projects

TL;DR

This work addresses the governance gap in software projects that include diverse human contributors and AI-powered agents. It proposes a domain-specific language (DSL) to define and enforce nuanced governance policies, supported by a three-part foundation: an abstract syntax via a governance metamodel, a concrete block-based syntax, and an operational semantics in the form of a decision engine. The PoC demonstrates a Python-based implementation with an ANTLR grammar to parse the concrete syntax and instantiate the metamodel, enabling policy deployment and automated decisions on platforms like GitHub. The roadmap outlines usability improvements, empirical evaluations, bias mitigation, and cross-domain applicability, signaling a path toward robust, automated, and inclusive governance in OSS and beyond.

Abstract

The stakeholders involved in software development are becoming increasingly diverse, with both human contributors from varied backgrounds and AI-powered agents collaborating together in the process. This situation presents unique governance challenges, particularly in Open-Source Software (OSS) projects, where explicit policies are often lacking or unclear. This paper presents the vision and foundational concepts for a novel Domain-Specific Language (DSL) designed to define and enforce rich governance policies in systems involving diverse stakeholders, including agents. This DSL offers a pathway towards more robust, adaptable, and ultimately automated governance, paving the way for more effective collaboration in software projects, especially OSS ones.

Figures (1)

• Figure 1: Abstract syntax metamodel of our DSL.