Remodularization Analysis Using Semantic Clustering - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Remodularization Analysis Using Semantic Clustering

Abstract

In this paper, we report an experience on using and adapting Semantic Clustering to evaluate software remodularizations. Semantic Clustering is an approach that relies on information retrieval and clustering techniques to extract sets of similar classes in a system, according to their vocabularies. We adapted Semantic Clustering to support remodularization analysis. We evaluate our adaptation using six real-world remodularizations of four software systems. We report that Semantic Clustering and conceptual metrics can be used to express and explain the intention of the architects when performing common modularization operators, such as module decomposition.
Fichier principal
Vignette du fichier
2014_csmrwcre_clustering preprint.pdf (265.03 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-00904409 , version 1 (17-10-2016)

Identifiers

Cite

Gustavo Santos, Marco Tulio Valente, Nicolas Anquetil. Remodularization Analysis Using Semantic Clustering. 1st CSMR-WCRE Software Evolution Week, Feb 2014, Antwerp, Belgium. ⟨10.1109/CSMR-WCRE.2014.6747174⟩. ⟨hal-00904409⟩
201 View
921 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More