Knowledge Engineering Architecture for the Analysis of Organizational Log Data: a software tool for log data analysis

Organisation log data are generate by software and can provide help to maintenance team addressing issues reported by the client. Once an application is in production, there are defects and other issues that need to be handled. This is also cause by customisation and maintenance of the software. That can compromise software integrity and functionality. This happening in production environment which the maintenance team don’t have access becomes a difficult to resolve. The issue must be handling in development environment which causes a condition to understand the problem in order to be able to fix it. To help with this, using log data from production to trace actions that occur of the issue. The log data doesn’t contain any of private data; it only contains actions events as a result of software usage. The main objective of this thesis work is to build a framework for an automatic log analyser to assist maintenance team addressing software issues. This framework also provides a knowledge management system allowing registering tacit experience into explicit knowledge. A prototype was developed to produce metrics and make a proof of this framework. This was done on a real environment and is related to a software migration project which means transferring data between databases that holds company business