Semi-Automatic Mapping Technique Using Snowballing to Support Massive Literature Searches in Software Engineering

Abstract

Systematic literature reviews represent an important methodology in Evidence-Based Software Engineering. To define the methodological route in these type of studies, in which a review of quantitative and qualitative aspects of primary studies is carried out to summarize the existing information regarding a particular topic, researchers use protocols that guide the construction of knowledge from research questions. This article presents a process that uses forward Snowballing, which identifies the articles cited in the paper under study and the number of citations as inclusion criteria to complement systematic literature reviews. A process that relies on software tools was designed to apply the Snowballing strategy and to identify the most cited works and those who cite them. To validate the process, a review identified in the literature was used. After comparing the results, new works that were not taken into account but made contributions to the subject of study emerged. The citation index represents the number of times a publication has been referenced in other documents and is used as a mechanism to analyze, measure, or quantitatively assess the impact of said publication on the scientific community. The present study showed how applying Snowballing along with other strategies enables the emergence of works that may be relevant for an investigation given the citations rate. That is, implementing this proposal will allow updating or expanding systematic literature studies through the new works evidenced.

Keywords

• citation impact
• evidence-based software engineering
• massive literature searches
• snowballing
• software engineering
• systematic mapping