SEApr 7

Proof of Concept as a First-Class Architectural Decision Instrument

arXiv:2604.058356.4
Predicted impact top 94% in SE · last 90 daysOriginality Incremental advance
AI Analysis

This addresses a methodological gap in software architecture practice, offering a systematic approach for practitioners, though it is incremental in refining existing concepts.

This paper tackles the problem of Proofs of Concept (PoCs) being underdefined and ad hoc in software engineering by providing a refined definition and a structured framework for PoC development, positioning them as first-class architectural decision instruments to improve decision quality and traceability.

Proofs of Concept (PoCs) are widely adopted practices in software engineering. Despite their relevance, PoCs remain conceptually underdefined and methodologically ad hoc in both research and industry, with definitions and implementation approaches that often lack clarity and consistency. This paper investigates the concept of PoCs with two complementary goals: (1) to provide a refined definition and astructured framework for PoC development grounded in a systematic review of academic and grey literature; and (2) to position PoCs as first-class architectural decision instruments rather than informal experiments or disposable artifacts. Through a systematic review of academic and grey literature we identify the key characteristics, processes, associated with PoCs and expose a significant gap the academic literature describes PoC outcomes but rarely its process. By synthesizing insights from diverse sources we propose a refined definition and a lightweight, three-phase framework (planning, execution, decision-making) that encompasses technical validation and explicit decision traceability. We also introduce the Undocumented Architectural Experiment anti-pattern, arising when PoCs influence high-impact architectural decisions without leaving durable architectural knowledge. We argue that elevating PoCs to first-class status improves decision quality, enhances traceability, and supports more systematic learning in architectural practice.

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