SOCIAL METRICS INCLUDED IN PREDICTION MODELS ON SOFTWARE ENGINEERING: A MAPPING STUDY
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This document discusses a mapping study on the use of social metrics in software engineering prediction models. It aims to identify which social metrics have been used and whether they had a positive effect. The study found that social metrics were often classified under other dimensions and there was inconsistent terminology. It identified papers reporting on various social metrics and grouped them into categories and sub-categories. The results showed that most papers reported social metrics had a positive effect in prediction models, while some reported negative or neutral effects. The conclusions note more research is needed on social metrics in different contexts and using larger datasets.
SOCIAL METRICS INCLUDED IN PREDICTION MODELS ON SOFTWARE ENGINEERING: A MAPPING STUDY
- 1. SOCIAL METRICS INCLUDED IN PREDICTION MODELS ON SOFTWARE ENGINEERING: A MAPPING STUDY Igor Wiese, Filipe Côgo, Reginaldo Ré, Igor Steinmacher and Marco Aurélio Gerosa
- 2. 2 MOTIVATION SCENARIO Subsystem A Class a Class c Class b Subsystem B Class d Class e Software systems are composed by Artifacts that dependes one each other HISTORICAL SIDE
- 3. 3 PROBLEM STATEMENT Even when social metrics were considered, they were classified as part of other dimensions, such as process, history, or change. Is not clear yet which social metrics are used in prediction models and what are the results of their use in different contexts.
- 5. 5 RESEARCH QUESTION Which social metrics were used in prediction models? Did the social metrics have positive effect when they were considered as predictor? RQ1 RQ2 We found that previous SLR did not discussed explicitly about social metrics inconsistent terminology for classifying social metrics and often do not report their individual result we identified papers describing evidences about the effects of social metrics we summarized the proposed classification, linking each group of metrics to the applicability of prediction models we mapped in which application each group of social metrics were used so far
- 6. 6 SNOWBALLING PROCESS METHOD Papers that explicitly mention only code metrics, objected oriented metrics, or static metrics
- 7. 7 DATA EXTRACTION ICSE 10 papers FSE 6 papers PROMISE 5 papers 48 Primary Papers, 103 distinct authors
- 8. 8 RQ1: WHICH SOCIAL METRICS WERE USED IN PREDICTION MODELS?
- 9. 9 RQ1: WHICH SOCIAL METRICS WERE USED IN PREDICTION MODELS? Group (3) Category (9) Sub-category (51)
- 10. 10 RQ1: WHICH SOCIAL METRICS WERE USED IN PREDICTION MODELS?
- 11. 11 RQ1: WHICH SOCIAL METRICS WERE USED IN PREDICTION MODELS?
- 12. 12 RQ2: DID THE SOCIAL METRICS HAVE POSITIVE EFFECT WHEN THEY WERE CONSIDERED AS PREDICTOR? 6 papers reported negative effects 21 papers reported positive effects 2 papers reported neutral effects
- 13. 13 RQ2: DID THE SOCIAL METRICS HAVE POSITIVE EFFECT WHEN THEY WERE CONSIDERED AS PREDICTOR?
- 14. CONCLUSIONS • social metrics were classified as part of other dimension, such as process, history, or change • Considering the results published so far, it could be risky to draw generalized conclusions about social metrics. • New opportunities of research concerning social metrics • different techniques and limited number of software projects in different contexts. • To consider large scale and longitudinal analysis • To investigate the effectiveness of social metrics to build prediction models 14
- 15. OUR RESEARCH 15 Artifacts a1 Artifacts a2 time Change coupling commit A change dependency indicates that two artifacts changed together (co-changed) in the past, making them evolutionarily connected
- 16. 16 PROBLEM STATEMENT File a1 File a2 time Change coupling commit + SOCIAL + HISTORICAL D´ambros - benchmark Tracy hall - SLR, etc D´ambros – OSS Kirbas/Ayse Bener – Industrial Gustavo Oliva, Markus Geipel