Towards Enabling An Artificial Self-Construction Software Life-cycle via Autopoietic Architectures

TL;DR

This paper advocates for a new paradigm in software engineering, inspired by Artificial Life, proposing self-constructing architectures enabled by foundation models to autonomously evolve and maintain software systems.

Contribution

It introduces the concept of Autopoietic Architectures, specifically Psi-Arch, as a foundational framework for self-constructing software, highlighting core challenges and potential research directions.

Findings

Analysis of limitations in traditional SDLC maintenance

Identification of key challenges in achieving self-construction

Proposal of a research agenda for self-constructing software architectures

Abstract

Software engineering research has focused on automating maintenance and evolution processes to reduce costs and improve reliability. The emergence of foundation models (FMs) with strong code understanding and reasoning abilities offers new opportunities for autonomous software behavior. Inspired by Artificial Life (ALife), we propose a fundamental shift in the Software Development Life-Cycle (SDLC) by introducing self-construction mechanisms that enable software to evolve and maintain autonomously. This position paper explores the potential of Autopoietic Architectures, specifically Psi-Arch, as a foundational framework for self-constructing software. We first analyze the limitations of traditional maintenance approaches and identify gaps in current SDLC automation. Subsequently, we outline the core challenges in achieving self-construction, including the integration of foundation-model-based reasoning units and the establishment of novel architectural paradigms. Although this paper does not present a definitive solution, it seeks to catalyze discourse and inspire research toward a new paradigm in software engineering, one in which self-constructing software represents the next frontier in SDLC automation.