| Title | Should I Bug You? Identifying Domain Experts in Software Projects Using Code Complexity Metrics |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Teusner, R., Matthies, C., Giese, P. |
| Conference Name | 2017 IEEE International Conference on Software Quality, Reliability and Security (QRS) |
| Date Published | jul |
| Keywords | code complexity metrics, collective code knowledge, Companies, complex software system, Complexity theory, Computer bugs, Computing Theory, Couplings, data mining, domain experts, expert identification, Measurement, Metrics, object-oriented programming, ownership high, pubcrawl, security metrics, Software, software components, software metrics, software projects, software quality |
| Abstract | In any sufficiently complex software system there are experts, having a deeper understanding of parts of the system than others. However, it is not always clear who these experts are and which particular parts of the system they can provide help with. We propose a framework to elicit the expertise of developers and recommend experts by analyzing complexity measures over time. Furthermore, teams can detect those parts of the software for which currently no, or only few experts exist and take preventive actions to keep the collective code knowledge and ownership high. We employed the developed approach at a medium-sized company. The results were evaluated with a survey, comparing the perceived and the computed expertise of developers. We show that aggregated code metrics can be used to identify experts for different software components. The identified experts were rated as acceptable candidates by developers in over 90% of all cases. |
| DOI | 10.1109/QRS.2017.51 |
| Citation Key | teusner_should_2017 |
Should I Bug You? Identifying Domain Experts in Software Projects Using Code Complexity Metrics