Operationalizing Software Engineering Theories for Practical Validation
Isaque Alves, Fabio Kon, Jessica Diaz, Carla Rocha

TL;DR
This paper presents a systematic, evidence-based procedure for operationalizing software engineering theories, bridging the gap between abstract concepts and empirical validation for practical utility.
Contribution
It extends existing frameworks by providing a clear, replicable guideline for operationalization, including variable definition, indicator selection, and hypothesis formulation.
Findings
Provides a formalized operationalization procedure for software engineering theories.
Demonstrates the procedure using the DevOps Team Taxonomies Theory.
Ensures a transparent chain of evidence from theory to empirical testing.
Abstract
Software Engineering often adapts theory-building frameworks from the social sciences to address socio-technical complexity. The key phases of the theory-building process are conceptual development, operationalization, testing, and application. Operationalization translates abstract concepts into measurable elements for empirical validation. This phase is essential for delivering the practical utility required by an applied science like Software Engineering. We propose a systematic procedure for the operationalization phase that bridges the gap between abstract concepts and empirical validation, ensuring the resulting theory is both rigorous and practically useful. We extend the operationalization framework proposed by Sj{\o}berg et al. and formulate non-causal hypotheses following Dubin's approach. Our procedure defines variables, selects indicators, and systematically derives…
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