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Sergio Gil-Borrás

Publications and source records attributed to Sergio Gil-Borrás.

2 recordsLinked to original sources

Theory building in software engineering: Operationalization

This work is part of a research project whose ultimate goal is to systematize a procedure for constructing theories in software engineering. The proposed methodology involves four phases: conceptualization, operationalization, testing, and application. In previous work, we described the conceptualization process. This paper presents a set of procedures for systematizing the operationalization phase in theory building. Specifically, it translates the concepts and propositions obtained from the previous conceptualization into constructs and empirically testable hypotheses. The operationalization phase is structured across three distinct dimensions: the practical procedural steps, their strict formal mathematical specification, and their evaluation through an illustrative empirical case study. Grounded in critical realism, we operationalize the qualitatively derived concepts and propositions into explicit constructs and logical hypotheses. It is important to emphasize that a novel strategy has been designed that reduces the number of hypotheses resulting from this process. In the use case described, more than 30% of the initial hypotheses have been eliminated because they are redundant. This paper is a pioneering contribution in offering comprehensive guidelines for theory operationalization using logical implication and describes a strategy based on graph theory that tackles the problem of hypothesis explosion and maintains the principle of parsimony.

cs.SE↗

Methodological Harness in Agentic Software Engineering: An Empirical Study on Mining Software Repositories

Context. Agentic software engineering requires mechanisms to coordinate and govern agents' work. The framework motivating this study proposes a methodological harness with eight mechanisms: context engineering, persistent shared knowledge, executable specifications, N-version mindset and parallel agents, normative specifications, structured consultation, evidence-based acceptance, and graduated autonomy. These are realized through artifacts such as rule or context files, specifications, and architectural decision records, but the framework had not been empirically validated at repository scale. Objective. We analyze to what extent and how this harness is observable in repositories with agentic activity. RQ1 characterizes adoption through artifact prevalence, breadth, co-occurrence, and temporal evolution; RQ2 examines rule files - a key observable artifact and persistent source of agent instructions - to assess how their content reflects the proposed mechanisms. Method. From the AIDev dataset of 116,211 GitHub repositories, we analyzed 5,435 using a design stratified by visibility, measured through stars as an indicator of popularity and/or reputation. For RQ1, we detected and quantified artifacts and introduction dates for the seven observable mechanisms. For RQ2, we qualitatively coded rule files from 150 repositories. Results. Population prevalence of at least one mechanism is 21.7%, versus 65.3% among the most visible repositories. Multi-mechanism configurations are rare. Where rule files exist, they almost always guide the agent and state norms, while persistent shared knowledge, executable specifications, structured consultation, and graduated autonomy appear only in a minority. Conclusions. The harness is empirically observable, but mainly through isolated mechanisms rather than the integrated system proposed by the framework.

cs.SE↗