Name
Abstract | ||
|---|---|---|
An essential characteristic of a software system, which is strongly related to its quality and has a major impact on program comprehension, is coupling. The coupling between software components also significantly influences the maintenance and evolution. We propose in this paper a coupling measure for Object-Oriented (OO) software systems which quantifies conceptual coupling of application classes. Conceptual coupling measures how the sources of different software entities (components, classes, modules, etc.) relate to each other, considering the textual information (identifiers, comments, etc.) contained in the code. We express the conceptual relationship between two software entities using an unsupervisedly learned high-dimensional representation of their text descriptions. Several experiments are conducted to emphasize that the proposed conceptual coupling measure expresses other aspects of coupling than the structural coupling measures and to also test its effectiveness for software restructuring at package level. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/SYNASC.2017.00047 | 2017 19th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC) |
Keywords | Field | DocType |
coupling measurement,conceptual coupling,unsupervised learning,doc2vec | Coupling,Identifier,Computer science,Software system,Theoretical computer science,Software,Unsupervised learning,Component-based software engineering,Program comprehension,Software measurement | Conference |
ISSN | ISBN | Citations |
2470-8801 | 978-1-5386-2627-6 | 0 |
PageRank | References | Authors |
0.34 | 18 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Diana-Lucia Miholca | 1 | 7 | 3.47 |
| Gabriela Czibula | 2 | 80 | 19.53 |
| Zsuzsanna Marian | 3 | 42 | 3.71 |
| István Gergely Czibula | 4 | 91 | 11.79 |