Day by day the number of organizations is increasing which using process mining to understand the way of execution of operational processes. For ssystematically drive the innovation in the digitalized world is used by Process Mining. The aim of Process mining is to get the knowledge of an organization's business processes by transforming the event data recorded in information systems. This leads to improve process performance or compliance to organization standards where process mining analysis is implemented. Process Mining techniques are relying on the existence of event data. We require putting too many efforts on making our systems to record historic data at all. The need to understand and improve their processes of businesses requires the process analysis techniques. This paper presents an approach how software event log is analyzed to understand & improve the software process by using classification which later used for the software code clone optimization.

1. W. M. P. van der Aalst. Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer-Verlag, Berlin, 2011
2. W. M. P. van der Aalst, A. J. M. M. Weijters, and L. Maruster. Workflow Mining: Discovering Process Models from Event Logs. IEEE Transactions on Knowledge and Data Engineering, 16(9):1128-1142, 2004
3. Adriansyah, A. , van Dongen, B. F. , van der Aalst, W. M. P. : Towards robust conformance checking. In: Business Process Management Workshops, Lecture Notes in Business Information Processing, vol. 66, pp. 122-133. Springer Berlin Heidelberg 2011
4. W. M. P. van der Aalst and C. Stahl. Modeling Business Processes: A Petri Net Oriented Approach. MIT press, Cambridge, MA, 2011
5. W. M. P. van der Aalst. Data Scientist: The Engineer of the Future. In K. Mertins, F. Benaben, R. Poler, and J. Bourrieres, editors,Proceedings of the I-ESA Conference, volume 7 of Enterprise Interoperability, pages 13-28. Springer-Verlag, Berlin, 2014
6. W. M. P. van der Aalst, A. J. Mooij, C. Stahl, and K. Wolf. Service Interaction: Patterns, Formalization, and Analysis. In M. Bernardo, L. Padovani, and G. Zavattaro, editors, Formal Methods for Web Services, volume 5569 of Lecture Notes in Computer Science, pages 42-88. Springer-Verlag, Berlin, 2009
7. W. M. P. van der Aalst, V. Rubin, H. M. W. Verbeek, B. F. van Dongen, E. Kindler, and C. W. Gunther. Process Mining: A Two-Step Approach to Balance Between Under_tting and Over_tting. Software and Systems Modeling, 9(1):87-111, 2010
8. R. Agrawal, D. Gunopulos, and F. Leymann. Mining Process Models from Workow Logs. In Sixth International Conference on Extending Database Technology, volume 1377 of Lecture Notes in Computer Science, pages 469{483. Springer-Verlag, Berlin, 1998
9. J. vom Brocke and M. Rosemann, editors. Handbook on Business Process Management, International Handbooks on Information Systems. Springer-Verlag, Berlin, 2010
10. T. Calders, C. Guenther, M. Pechenizkiy, and A. Rozinat. Using Minimum Description Length for Process Mining. In ACM Symposium on Applied Computing (SAC 2009), pages 1451{1455. ACM Press, 2009

Process Mining Prom Ioe (internet Of Events) Clone Clone Optimization.