Reasoning Beyond Prediction: From Data-Driven to Causal Software Engineering

2026-06-26

AI Summary

Current data-driven approaches in software engineering are largely confined to pattern prediction and struggle to support the deep reasoning and decision-making required for developing complex systems. This work proposes a novel human-AI collaboration paradigm that integrates deep learning with causal inference, establishing a software engineering framework capable of causal modeling and reasoning. By doing so, the approach enables machines to transition from mere predictive assistance to cognitive augmentation. The resulting framework equips software engineers with interpretable, causally grounded decision support, significantly enhancing both the efficiency and quality of developing complex software systems—particularly those that are AI-driven, distributed, or embedded.

Abstract

Software engineering is an intellectually demanding, creative discipline that juggles a web of interdependent tasks to design, build, and assure the quality of increasingly complex systems. As our expectations from software soar - with demands spanning AI-driven products, pervasively distributed and cloud-native architectures, and deeply embedded cyber-physical environments - its complexity steadily increases. In response, a new wave of co-engineering methods and tools, fueled by deep learning, has emerged to augment the process, enhancing automation and decision support. Yet, these advances remain far from delivering the kind of intelligent support that modern software development demands. We call for a new paradigm of human-machine cooperation: one where machines don't just automate routine tasks or predict from learned patterns, but actively amplify engineers' reasoning through the lens of causation. As software becomes smarter, a smarter support is needed.

Problem

• causal reasoning
• software engineering
• human-machine cooperation
• intelligent support
• complex systems

Innovation

• causal reasoning
• software engineering
• human-machine cooperation
• deep learning
• intelligent decision support