Proof of Concept as a First-Class Architectural Decision Instrument

TL;DR

This paper refines the definition of Proof of Concept (PoC) in software engineering, proposing a structured framework and positioning PoCs as essential architectural decision tools to improve traceability and decision quality.

Contribution

It provides a systematic review, a refined PoC definition, and a lightweight three-phase framework positioning PoCs as first-class architectural decision instruments.

Findings

Identified key characteristics and processes of PoCs.

Proposed a three-phase framework: planning, execution, decision-making.

Highlighted the Undocumented Architectural Experiment anti-pattern.

Abstract

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.