Social metrics included in prediction models on software engineering: A mapping study

Igor Scaliante Wiese, Filipe Roseiro Côgo, Reginaldo Ré, Igor Steinmacher, Marco Aurélio Gerosa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Context: Previous work that used prediction models on Software Engineering included few social metrics as predictors, even though many researchers argue that Software Engineering is a social activity. Even when social metrics were considered, they were classified as part of other dimensions, such as process, history, or change. Moreover, few papers report the individual effects of social metrics. Thus, it is not clear yet which social metrics are used in prediction models and what are the results of their use in different contexts. Objective: To identify, characterize, and classify social metrics included in prediction models reported in the literature. Method: We conducted a mapping study (MS) using a snowballing citation analysis. We built an initial seed list adapting strings of two previous systematic reviews on software prediction models. After that, we conducted backward and forward citation analysis using the initial seed list. Finally, we visited the profile of each distinct author identified in the previous steps and contacted each author that published more than 2 papers to ask for additional candidate studies. Results: We identified 48 primary studies and 51 social metrics. We organized the metrics into nine categories, which were divided into three groups-communication, project, and commit-related. We also mapped the applications of each group of metrics, indicating their positive or negative effects. Conclusions: This mapping may support researchers and practitioners to build their prediction models considering more social metrics

Original languageEnglish (US)
Title of host publication10th International Conference on Predictive Models in Software Engineering, PROMISE 2014
PublisherAssociation for Computing Machinery
Pages72-81
Number of pages10
ISBN (Print)9781450328982
DOIs
StatePublished - 2014
Externally publishedYes
Event10th International Conference on Predictive Models in Software Engineering, PROMISE 2014 - Turin, Italy
Duration: Sep 17 2014Sep 17 2014

Publication series

NameACM International Conference Proceeding Series

Conference

Conference10th International Conference on Predictive Models in Software Engineering, PROMISE 2014
Country/TerritoryItaly
CityTurin
Period9/17/149/17/14

Keywords

  • Mapping study
  • Prediction models
  • Social metrics
  • Social network analysis

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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