Title
Identifying Crosscutting Concerns Using Fan-In Analysis
Abstract
Aspect mining is a reverse engineering process that aims at finding crosscutting concerns in existing systems. This article proposes an aspect mining approach based on determining methods that are called from many different places, and hence have a high fan-in, which can be seen as a symptom of crosscutting functionality. The approach is semiautomatic, and consists of three steps: metric calculation, method filtering, and call site analysis. Carrying out these steps is an interactive process supported by an Eclipse plug-in called FINT. Fan-in analysis has been applied to three open source Java systems, totaling around 200,000 lines of code. The most interesting concerns identified are discussed in detail, which includes several concerns not previously discussed in the aspect-oriented literature. The results show that a significant number of crosscutting concerns can be recognized using fan-in analysis, and each of the three steps can be supported by tools.
Year
DOI
Venue
2007
10.1145/1314493.1314496
ACM Transactions on Software Engineering and Methodology (TOSEM)
Keywords
DocType
Volume
crosscutting concern,high fan-in,call site analysis,interactive process,aspect-oriented programming,fan-in analysis,aspect mining,crosscutting functionality,reverse engineering,additional key words and phrases: aspect-oriented programming,crosscutting concerns,reverse engineering process,aspect mining approach,aspect-oriented literature,fan-in metric
Journal
17
Issue
ISSN
Citations 
1
ACM Transactions on Software Engineering and Methodology, 2007
34
PageRank 
References 
Authors
1.03
35
3
Name
Order
Citations
PageRank
Marius Marin127013.70
A. van Deursen24034254.98
Leon Moonen3143272.21