Investigating the use of lexical information for software system clustering

Developers have a lot of freedom in writing comments as well as in choosing identifiers and method names. These are intentional in nature and provide a different relevance of information to understand what a software system implements, and in particular the role of each source file. In this paper we...

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Bibliographic Details
Main Authors: Corazza, A., Di Martino, Sergio, Maggio, V., Scanniello, G.
Format: Conference Proceeding
Language:English
Subjects:
Clustering
Clustering algorithms
Java
Lexical Information
Partitioning algorithms
Probabilistic logic
Probabilistic Model
Software algorithms
Software Remodularization
Software systems
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Summary:Developers have a lot of freedom in writing comments as well as in choosing identifiers and method names. These are intentional in nature and provide a different relevance of information to understand what a software system implements, and in particular the role of each source file. In this paper we investigate the effectiveness of exploiting lexical information for software system clustering. In particular we explore the contribution of the combined use of six different dictionaries, corresponding to the six parts of the source code where programmers introduce lexical information, namely: class, attribute, method and parameter names, comments, and source code statements. Their relevance has been weighted by means of a probabilistic model, whose parameters have been estimated by the Expectation-Maximization algorithm. To group source files accordingly we used a hierarchical clustering algorithm. The investigation has been conducted on a dataset of 13 open source Java software systems.
ISSN:1534-5351
2640-7574
DOI:10.1109/CSMR.2011.8