A Strategy to Support Replications of Controlled Experiments in Software Engineering

Abstract

Replication is essential to build knowledge in empirical science. Experiment replications reported in the software engineering context present variabilities on their experiment elements, e.g., variables, materials. Further understanding these variabilities could help planning lack of strategy to support the representation of experiment variabilities and commonalities. In addition, there is also a gap related to effective reuse and traceability of experiment elements. These problems are likely to hamper the replication understanding and planning. In order to overcome these gaps, we intend to create a conceptual model and a tool to support replication planning. To develop these solutions, we will use concepts of experimentation and software product lines. Our idea is to build a core structure which allows the configuration of experiment elements based commonalities with previous replications and desired variabilities to fit the specific replication purposes. In this paper we describe related work, our research methodology, as well as the current research progress and expected future contributions.