Digital Twins for Software Engineering Processes

2025-10-07

AI Summary

Low expert time utilization and difficulty for domain experts to produce high-quality software hinder software engineering (SE) efficiency and quality. Method: This paper proposes the Software Engineering Process Digital Twin (SE-DT) framework—a dynamic, co-evolving virtual replica of collaborative development—integrating runtime system modeling, real-time acquisition of heterogeneous multi-source data, process mining, and closed-loop feedback control. Contribution/Results: We formally define SE-DT’s architectural characteristics, core components, and essential capabilities for process understanding, bottleneck identification, and collaboration optimization. We systematically identify and analyze critical research gaps—including data fusion, semantic alignment, lightweight modeling, and trustworthy feedback—and outline corresponding technical pathways. This work establishes foundational theoretical and practical support for SE-DT development and deployment, advancing the digital transformation of software engineering processes.

Technology Category

• Application Domains: Software Engineering
• Data Mining & Knowledge Management: Representing, Reasoning, and Using Provenance, Trust
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Web Mining and Content Analysis: Models for Web evolution
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

Digital twins promise a better understanding and use of complex systems. To this end, they represent these systems at their runtime and may interact with them to control their processes. Software engineering is a wicked challenge in which stakeholders from many domains collaborate to produce software artifacts together. In the presence of skilled software engineer shortage, our vision is to leverage DTs as means for better rep- resenting, understanding, and optimizing software engineering processes to (i) enable software experts making the best use of their time and (ii) support domain experts in producing high-quality software. This paper outlines why this would be beneficial, what such a digital twin could look like, and what is missing for realizing and deploying software engineering digital twins.

Problem

• Digital twins model software engineering processes for optimization
• Address skilled engineer shortage through improved process representation
• Enable experts to efficiently produce high-quality software artifacts

Innovation

• Digital Twins represent runtime software engineering processes
• Digital Twins interact with systems to control processes
• Digital Twins optimize software engineering for better resource utilization