| human | Q5 |
| Q83804234 | Almost There: A Study on Quasi-Contributors in Open-Source Software Projects |
| Q58051413 | An Empirical Study of the Relation Between Strong Change Coupling and Defects Using History and Social Metrics in the Apache Aries Project |
| Q58051487 | An Extensible Service for Experts Recommendation on Distributed Software Development Projects |
| Q58051421 | Do historical metrics and developers communication aid to predict change couplings? |
| Q58051429 | Increasing the Self-Efficacy of Newcomers to Open Source Software Projects |
| Q58051507 | Newcomers Withdrawal in Open Source Software Projects: Analysis of Hadoop Common Project |
| Q58051432 | Predicting Change Propagation from Repository Information |
| Q58051510 | Prediction of Developer Participation in Issues of Open Source Projects |
| Q58051516 | Recommending mentors to software project newcomers |
| Q58051450 | Social metrics included in prediction models on software engineering |
| Q83804747 | The hard life of open source software project newcomers |
| Q58051454 | Using Structural Holes Metrics from Communication Networks to Predict Change Dependencies |
| Q58051470 | What can commit metadata tell us about design degradation? |
| Q58051477 | Why do newcomers abandon open source software projects? |
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