Grupo Alarcos · Journal article · 2026
An ontology-based metamodel for the analysis and management of social debt in software development teams
Eydy del Carmen Suárez Brieva, César Jesús Pardo Calvache, Ricardo Pérez del Castillo
Social debt in software development refers to unforeseen costs and adverse consequences arising from deficiencies in communication, coordination, collaboration, organizational structures, or decision-making. This debt disrupts the team’s socio-technical balance, leading to interpersonal tension, workload imbalance, loss of cohesion, and deteriorated project performance. Despite its relevance, it lacks a formal and machine-interpretable representation for systematic analysis and automated decision-making. This study introduces the Social Debt Ontology, as a formal ontology-based metamodel that provides a structured vocabulary for representing causes, effects, community smells, mitigation strategies, indicators, metrics, risks, and processes. The ontology comprises 46 classes, 74 object properties, and 286 individuals, and was implemented in OWL 2 DL using Protégé following an adaptation of the REFSENO methodology. Validation was performed through competency questions expressed as SPARQL queries, with logical consistency verified using the HermiT reasoner and two case studies. Quality was assessed using the FOCA methodology, with attention to completeness, clarity, consistency, adaptability, and computational efficiency. The ontology enables automated reasoning, traceability between causes and effects, and ontology-based recommendations. By identifying communication failures, coordination bottlenecks, role ambiguity, knowledge concentration, and ineffective collaboration, the ontology supports timely corrective actions that may reduce rework, defects, delays, and knowledge loss, thereby improving software quality and team well-being. Overall, the ontology provides a reusable and robust conceptual framework for the systematic management of social debt.