Towards socio-cyber-physical systems: a software perspective amid AI breakthroughs

Abstract

Software technology is undergoing a paradigm shift driven by two converging trends. First, the scope of software responsibility has expanded significantly: as “software-defined everything” becomes a reality, software has evolved into the integration core of sociocyber-physical systems (SCPSs). Second, the capabilities and development methods of software are being greatly enhanced by recent breakthroughs in artificial intelligence (AI). This article presents perspectives and observations on software engineering in this era of rapid progress. We aim to outline a set of foundational challenges in engineering SCPSs and highlight the need for innovative software solutions that extend beyond AI technologies alone. Specifically, we examine the need for a new paradigm that can address the complexities introduced by SCPSs, which challenge conventional paradigms through the blurring of system boundaries, continuous lifecycle evolution, and the embracing of inherent uncertainty. We highlight new engineering principles of socio-technical co-design, cyber-physical integration, and development-operation convergence, and a knowledge- and data-driven approach to taming uncertainty. Emerging proposals, including digital humanism, agentic SCPS, ubiquitous operating system, and continuous quality assurance, are discussed alongside possible extensions to existing technologies. We then outline key research directions for both runtime support and quality assurance. On the runtime side, we argue for a new generation of software infrastructure for SCPSs, including unified hardware abstractions, scalable and resilient runtime systems, AI-enabled system management, and human-centric operating system primitives. On the assurance side, we highlight the need for new approaches combining unified socio-cyber-physical modeling, specification of both technical and non-technical properties, data-driven simulation and testing, continuous verification, and runtime monitoring under uncertainty. Furthermore, we present specific challenges within key application domains, including intelligent vehicles, smart manufacturing, and smart cities. In doing so, we aim to stimulate discussion within the software engineering community and encourage support from industry and government to address the critical engineering and governance issues inherent to this new generation of systems.