Method for automatic detection of the reasons of unusual system behavior by evaluation of correlation between events in monitoring tool

This article describes the method related to simplifying detection of the problem reason in applications by using automatic analyzing of monitoring data on embedded system. Usually, dependencies in monitoring data are not obvious and usually it is very complicated to find the relationship between error symptom and the reason of the problem. The suggested method finds dependencies in system behavior automatically that gets the chance to detect hidden reasons of the problem in huge amount of monitoring data. In particular, the proposed method detects the unusual system behavior and tries to find the most probable reason of such behavior by using statistical data mining algorithms. It structures monitoring data by special way and most probable reason of the problem is colored by monitoring tool to help the developer to analyze the system behavior more comfortable and more precise. The experiments show that this method can detect a wide set of problems in system behavior that accelerates and improves the analysis of system behavior according to monitoring information.