Collaboration patterns in software developer network
In this entry, we mine collaboration patterns from a large software developer network (Surian et al. 2010). We consider high- and low-level patterns. High-level patterns correspond to various network-level statistics that we observe to hold in this network. Low-level patterns are topological subgrap...
Saved in:
| Main Authors: | , , |
|---|---|
| 格式: | text |
| 語言: | English |
| 出版: |
Institutional Knowledge at Singapore Management University
2018
|
| 主題: | |
| 在線閱讀: | https://ink.library.smu.edu.sg/sis_research/4904 https://ink.library.smu.edu.sg/context/sis_research/article/5907/viewcontent/Collaboration_Patterns_in_Software_Developer_Network_av.pdf |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | Singapore Management University |
| 語言: | English |
| 總結: | In this entry, we mine collaboration patterns from a large software developer network (Surian et al. 2010). We consider high- and low-level patterns. High-level patterns correspond to various network-level statistics that we observe to hold in this network. Low-level patterns are topological subgraph patterns that are frequently observed among developers collaborating in the network. Mining topological subgraph patterns are difficult as it is an NP-hard problem. To address this issue, we use a combination of frequent subgraph mining and graph matching by leveraging the power law property exhibited by a large collaboration graph. The technique is applicable to any software developer network that could be represented as a large graph. As a case study, we experiment with a developer collaboration network extracted from SourceForge.Net, which is the most popular open-source software portal. |
|---|