PBFD and PDFD: Formally Defined and Verified Methodologies and Empirical Evaluation for Scalable Full-Stack Software Engineering

Dong Liu

公開日: 2025/8/18

Abstract

This paper introduces Primary Breadth-First Development (PBFD) and Primary Depth-First Development (PDFD), two formally defined and verified methodologies for scalable, industrial-grade full-stack software engineering. These approaches bridge a longstanding gap between formal methods and real-world development practice by enforcing structural correctness through graph-theoretic modeling. Unlike prior graph-based approaches, PBFD and PDFD operate over layered directed graphs and are formalized using unified state machines and Communicating Sequential Processes (CSP) to ensure critical properties, including bounded-refinement termination and structural completeness. To coordinate hierarchical data at scale, we propose Three-Level Encapsulation (TLE) - a novel, bitmask-based encoding scheme that delivers provably constant-time updates. TLE's formal guarantees underpin PBFD's industrial-scale performance and scalability. PBFD was empirically validated through an eight-year enterprise deployment, demonstrating over 20x faster development than Salesforce OmniScript and 7-8x faster query performance compared to conventional relational models. Additionally, both methodologies are supported by open-source MVPs, with PDFD's implementation conclusively demonstrating its correctness-first design principles. Together, PBFD and PDFD establish a reproducible, transparent framework that integrates formal verification into practical software development. All formal specifications, MVPs, and datasets are publicly available to foster academic research and industrial-grade adoption.