Table of Contents

The algorithm was developed by Periklis Andritsos and Vassilios Tzerpos.

To generate decompositions that exhibit the least information lost when entities are represented by their clusters.

The factbase is a generic dependency data table where each row describes one entity to be clustered. Each column contains the value for a specific attribute.

The Limbo algorithm produces software decompositions with minimum information loss.

An agglomerative clustering algorithm that on each step merges the two clusters with the least information loss.

The information lost is calculated using the Agglomerative Information Bottleneck algorithm.

The LIMBO decomposition has a small value for its information lost function.

LIMBO has four phases:

- Creation of the Summary Artefacts
- Application of the AIB algorithm
- Associating original artefacts with clusters
- Determining the number of clusters

Last modified:

2010/05/06 10:12

2010/05/06 10:12