An Integrative Framework for Behavioral Software Engineering And AI-Augmented Architectural Evolution: Synthesizing Competence Models with Legacy System Refactoring

• Stewart Whitefield

  Global Institute for Software Research and Computational Intelligence, Zurich, Switzerland

  Author

The evolution of modern software engineering is increasingly characterized by a dual focus on human-centric behavioral competencies and automated technological advancement. This research presents a comprehensive, integrative framework that bridges the gap between behavioral software engineering-specifically competence modeling and human aspects-and the technical rigors of migrating legacy monolithic systems to cloud-native architectures. By synthesizing three decades of refactoring research with contemporary AI-augmented methodologies, the study addresses the critical challenge of managing technical debt while ensuring that the individual professional capability of engineers is aligned with industrial needs. We analyze the multidimensional nature of competence, incorporating cognitive, functional, and social dimensions to propose a roadmap for software assurance and individual capability enhancement. Simultaneously, the article investigates the taxonomy of service identification approaches, exploring how object-oriented source code can be materialized into component-based languages through inheritance transformation and instantiation. The research further evaluates the impact of cloud design patterns, deployment tracking, and exception monitoring on the sustainability of cloud-native applications. By providing a systematic literature review and empirical mapping of both human behaviors and technical modernization strategies, this study identifies a unified path for software development organizations to achieve architectural agility without sacrificing the psychological and behavioral foundations of the engineering process.

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