Name
Abstract | ||
|---|---|---|
Statistical properties of software networks have been extensively studied. However, in the previous works, software networks are usually considered as a single-layer network, which cannot capture the authentic characteristics of software since software in its nature should be multilayer. In this paper, we explore the structural properties of the multilayer software network at the class level by progressively merging layers together, where each coupling type such as inheritance, implements, and method call defines a specific layer. A case study in software Tomcat is conducted using a set of 10 measures widely used in complex network literatures. The results show that some structural properties that are widely observed in software network researches can only emerge when several layers are merged together, such as high clustering coefficient, small value of average shortest path length, and high global efficiency. Our study highlights the importance of taking into consideration the multilayer nature of software systems. The results we found can provide valuable insights to our understanding and modeling of the dynamical processes taking place in the design and development of software systems. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1142/S0219525918500042 | ADVANCES IN COMPLEX SYSTEMS |
Keywords | Field | DocType |
Multilayer network,software network,software structural analysis,complex network,Tomcat | Coupling,Shortest path problem,Theoretical computer science,Software,Artificial intelligence,Complex network,Clustering coefficient,Merge (version control),Mathematics,Machine learning | Journal |
Volume | Issue | ISSN |
21 | 2 | 0219-5259 |
Citations | PageRank | References |
0 | 0.34 | 23 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weifeng Pan | 1 | 107 | 16.47 |
| Bo Hu | 2 | 0 | 0.34 |
| Jilei Dong | 3 | 0 | 0.68 |
| Kun Liu | 4 | 57 | 15.38 |
| Bo Jiang | 5 | 9 | 3.25 |