Paper Info
Title
Clustering Based Automatic Refactorings Identification
Abstract
The aim of this paper is to approach the problemof improving the design of an object oriented software system, by identifying the appropriate refactorings. It is well known that improving the quality of software systems design is an important issue during the evolution of object oriented software systems. This improvement can be achieved by refactoring the software system in order to improve its internal structure, but without altering the external behavior of the code. In this paper we introduce a hierarchical divisive clustering algorithm for automatic identification of refactorings that improve the internalstructure of a software system. We evaluate our approach using JHotDraw case study and a real software system, emphasizing its advantages in comparison with existing similar approaches.
Year
DOI
Venue
2008
10.1109/SYNASC.2008.17
SYNASC
Keywords
Field
DocType
hierarchical divisive clustering algorithm,software system,important issue,external behavior,jhotdraw case study,real software system,automatic identification,software systems design,similar approach,appropriate refactorings,automatic refactorings identification,software maintenance,clustering,software quality,object oriented programming,refactoring,algorithm design and analysis,clustering algorithms,software systems,software design,data mining
Object-oriented design,Data mining,Computer science,Software system,Software maintenance,Software construction,Software verification and validation,Code refactoring,Software sizing,Software development
Conference
Citations 
PageRank 
References 
4
0.49
13
Authors
2
Name
Order
Citations
PageRank
István Gergely Czibula19111.79
Gabriela Czibula28019.53