Name
Abstract | ||
|---|---|---|
Coupling metrics play an important role in empirical software engineering research as well as in industrial measurement programs. The existing coupling metrics have usually been defined in a way that they can be computed from a static analysis of the source code. However, modern programs extensively use dynamic language features such as polymorphism and dynamic class loading that are difficult to capture by static analysis. Consequently, the derived metric values might not accurately reflect the state of a program. In this paper, we express existing definitions of coupling metrics using call graphs. We then compare the results of four different call graph construction algorithms with standard tool implementations of these metrics in an empirical study. Our results show important variations in coupling between standard and call graph-based calculations due to the support of dynamic features. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/SCAM.2010.25 | Source Code Analysis and Manipulation |
Keywords | Field | DocType |
call graphs,call graph,dynamic feature,coupling metrics,different call graph construction,existing coupling metrics,empirical software engineering research,dynamic language,dynamic class loading,empirical study,static analysis,software quality,polymorphism,software metrics,coupling,software engineering,couplings,java,measurement,graph theory,source code,metrics,empirical software engineering | Graph theory,Source code,Computer science,Static analysis,Theoretical computer science,Call graph,Software metric,Empirical process (process control model),Software quality,Empirical research | Conference |
ISSN | ISBN | Citations |
1942-5430 | 978-1-4244-8655-7 | 8 |
PageRank | References | Authors |
0.54 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Simon Allier | 1 | 64 | 5.19 |
| Stéphane Vaucher | 2 | 209 | 8.55 |
| Bruno Dufour | 3 | 174 | 9.95 |
| Houari Sahraoui | 4 | 801 | 42.47 |