1013 Process Implementation
Dott.mag. Alessio Cecconi
Contact details
Weekly hours
Language of instruction
11/18/19 to 11/29/19
Registration via LPIS
Notes to the course
Day Date Time Room
Tuesday 12/03/19 12:00 PM - 03:00 PM D3.0.222
Thursday 12/05/19 02:00 PM - 05:00 PM TC.3.12
Tuesday 12/10/19 02:30 PM - 05:30 PM D2.0.342 Teacher Training Raum
Thursday 12/12/19 02:00 PM - 05:00 PM TC.3.09
Tuesday 12/17/19 02:00 PM - 05:00 PM TC.4.12
Tuesday 01/14/20 02:30 PM - 05:30 PM TC.5.04
Thursday 01/16/20 02:00 PM - 05:00 PM TC.4.16
Tuesday 01/21/20 02:00 PM - 04:00 PM D3.0.225

The course covers the main concepts spanning over the topics of business process implementation and process mining. The treated arguments pertain: the characteristics and functionalities of Business Process Management Systems (BPMSs); the implementation, deployment and execution of business process models on BPMSs; the formal notions and fundamental properties of the executable semantics of models grounded in Petri nets; the fundamental algorithms of process mining, with a particular focus on the automated discovery of processes out of event logs.

Learning outcomes
Successful students will be able to put business process models into action by their enactment through IT systems. Furthermore, they will understand
the mechanisms that allow the machine-based discovery of process models out of recorded process executions.
Attendance requirements

This course is a PI type. It is possible to be absent in one class. In case you need to miss more than one class, this must be properly justified. Please promptly contact the instructor.

Students who miss the class are required to engage in self-study to catch up with the contents.

Teaching/learning method(s)

The course is designed as a mixture of lecture with accompanying project assignments.

Both theoretical contents and hands-on sessions will be held. Tools used in the course will include the BonitaSoft Business Process Management System and modeller (, the WoPeD workflow and Petri net modeller and analyser (, the ProM process mining toolkit (, and Celonis process mining platform (

A Virtual Machine based on the VirtualBox platform ( will be distributed with all the necessary software pre-installed.

The final grade is assigned on the basis of the following proportions:
60% - written exam
20% - group assignment on process implementation
20% - group assignment on process mining
Prerequisites for participation and waiting lists

Participants are expected to be familiar with the content of the course Business Process Management. Generally, it is assumed that the concepts
described in Dumas et al.: Fundamentals of Business Process Management, Springer 2013, are understood.

1 Author: Marlon Dumas, Marcello La Rosa, Jan Mendling, Hajo A. Reijers
Title: Fundamentals of Business Process Management

Publisher: Springer
Year: 2013
Content relevant for class examination: Yes
Recommendation: Essential reading for all students
Type: Book
2 Author: Wil M.P. van der Aalst
Title: Process Mining - Data Science in Action

Publisher: Springer
Edition: 2nd
Year: 2016
Content relevant for class examination: Yes
Content relevant for diploma examination: Yes
Recommendation: Essential reading for all students
Type: Book
Recommended previous knowledge and skills

It is required that the “Process Innovation” course has been already regularly attended, and that the following notions are already acquired:

  • Business Process Management (BPM), its initiative, goals, and life-cycle;
  • business process identification, discovery, analysis, and re-design;
  • business process modelling with BPMN.

Basic notions of set theory are recommended.

Availability of lecturer(s)
Please contact the lecturer via e-mail to fix an appointment.
Last edited: 2019-12-03