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--- start [2009/05/12 04:09] – mark
+++ start [2009/06/19 20:44] (current) – bil
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-====== Welcome to Software Clustering Encyclopedia ======
+====== Welcome to the Software Clustering Wiki ======
-Software clustering methods group entities of a software system, such as classes or
+The goal of this wiki is to host information about software clustering research. Everybody is welcome to contribute. If you are interested to add content, you can get an account by sending an email to [[mark@cse.yorku.ca|Mark Shtern]].
-source files, into subsystems, and compute views that will uncover buried facts about
-the software system.
+By using the links to the right, you can find out about software clustering algorithms and evaluation techniques published in the literature, as well as download tools for software clustering.
-Such methods have been successfully applied to solve many reverse engineering
+Feel free to contact us with any suggestions on how to make the Software Clustering Wiki more useful to you!
-problems. The amount of software clustering related research published
-in the literature these days demonstrates the importance that the research community places on the development of effective software clustering techniques.
-Research on software clustering has taken three directions:
-  - Development of better software clustering algorithms or the improvement of existing ones
-  - Evaluation of existing software clustering methods
-  - Investigation of further application for clustering methodologies in a software context
-====== Cluster Analysis ======
-Cluster Analysis is a group of multivariate techniques whose primary purpose is to
-group entities based on their attributes. Entities are classified according to
-predetermined selection criteria, so that similar objects are placed in the same cluster.
-The objective of any clustering algorithm is to sort entities into groups, so that the
-variation between clusters is maximized relative to variation within clusters.
-The typical stages of cluster analysis techniques are as follows:
-  - Fact Extraction and Filtering
-  - Analysis
-    - Compute resemblance coefficients
-    - Cluster Creation
-  - Results Visualization
-  - User Feedback Collection
-The process may now repeat until satisfactory results are obtained.