Applying Frequent Sequence Mining to Identify Design Flaws in Enterprise Software Systems

In this paper we show how frequent sequence mining (FSM) can be applied to data produced by monitoring distributed enterprise applications. In particular we show how we applied FSM to run-time paths to highlight repeating sequences of interest by using alternative support counting techniques. We show how the patterns identified, can be used to highlight design flaws in enterprise applications. We also discuss some algorithm scalability problems related to applying FSM to run-time paths and give solutions to these issues.

• Type: Conference
• Year: 2007
• Where: MLDM
• Authors: Trevor Parsons, John Murphy, Patrick O'Sullivan
• Keywords: Enterprise Applications, Frequent Sequence Mining, Machine Learning, MLDM 2007, Support Counting Techniques