Published February 23, 2026 | Version v1

IVP as a Meta-Principle: A Unifying Software Architecture Theory

  • 1. Independent Researcher

Description

Software architecture practitioners navigate a fragmented landscape of independent design principles (SOLID, Information Hiding, Package Principles, and others). This fragmentation leads to memorization over understanding and difficulty reasoning about novel situations. This paper presents the Independent Variation Principle (IVP) as a unifying meta-principle from which established architectural guidelines emerge as special cases. We provide a formal mathematical framework defining elements, dependencies, change drivers, and IVP compliance, enabling rigorous reasoning about architectural properties. Our Knowledge Theorem proves that maximal causal cohesion is equivalent to complete and pure embodied relevant causal domain knowledge, establishing that cohesion is fundamentally epistemic and reframing software architecture as epistemological knowledge work: organizing embodied domain knowledge (business rules, quality attributes, infrastructure) rather than merely managing dependencies. We prove bidirectional logical equivalence between IVP and all five SOLID principles (SRP, OCP, LSP, ISP, DIP), demonstrating that these principles are constrained instances of IVP applied at specific granularities. Each proof establishes both directions: applying IVP at the appropriate level necessarily yields the SOLID principle, and following the SOLID principle necessarily produces IVP-compliant structure. A quantitative case study on dependency inversion validates that IVP-based analysis correctly predicts design quality through measurable coupling and cohesion metrics. By unifying disparate principles under one theoretical framework, IVP enables practitioners to learn one foundational principle instead of dozens, offers educators a more efficient pedagogical approach, and provides tool developers a formal basis for automated analysis.

Files

IVP-ICSA2026-Research-article.pdf

Files (565.8 kB)

Name Size Download all
md5:d931d17ddff00fdb610b5b1e9c6b5568
199.1 kB Preview Download
md5:9e9c9dd05138e49a8774b98419f2c995
247.5 kB Preview Download
md5:9a3821b67be0bbed299bdbd0c4422230
119.1 kB Download

Additional details

Dates

Submitted
2025-11-26
1st version submitted
Submitted
2025-12-13
Final submitted preprint, rejected