Using Process Mining to Generate AI Agents from Software Engineering Process Records

2026-07-06

AI Summary

This study addresses the challenge of determining appropriate granularity and responsibility allocation for AI agents in human-AI collaborative software engineering. The authors propose a method that dynamically generates AI agent roles based on project-specific context by integrating object-centric process mining with both imperative and declarative process modeling. Leveraging event logs from software repositories, the approach automatically discovers agent structures aligned with the unique characteristics of a project’s development process and synthesizes corresponding specifications and implementations. Moving beyond predefined role templates, the method has been successfully deployed in prominent open-source projects. Empirical validation through functional testing and user studies demonstrates that the generated agents exhibit responsibility boundaries and collaboration efficiency closely matching developer expectations.

Abstract

Integrating AI agents into Software Engineering (SE) raises an important challenge: how can we specify and realize AI agents that work effectively alongside humans in hybrid SE teams? Determining the right granularity and separation of concerns for such agents is non-trivial. Coarse-grained agents may introduce unmanageable complexity, whereas micro-agents may create severe coordination overhead. Moreover, existing multi-agent SE frameworks typically rely on predefined role structures and do not account for project-specific characteristics or process adaptations. We address this by combining object-centric, imperative, and declarative process mining. Using event logs extracted from software repositories, our approach discovers project-specific agent roles using a predefined SE role vocabulary grounded in repository behavior and generates matching agent specifications and implementations. As proof-of-concept, we applied our approach to a well-established open-source project. We performed functional tests and an exploratory user study to determine how well the generated AI agent specifications are aligned with human expectations.

Problem

• AI agents
• Software Engineering
• Process Mining
• Role Specification
• Hybrid Teams

Innovation

• process mining
• AI agents
• software engineering
• role discovery
• hybrid teams