This page contains information on Bachelor-/Mastertheses that are currently available. This does not constitute a complete list. If you have a great idea that fits the scope of the Business Process Management Research Cluster feel free to contact our team at any time!
Extension of WoPeD tool with arc weights and coverability graph
Introduction. WoPeD (Workflow Petri Net Designer)  is an open-source software developed at the Cooperative State University Karlsruhe under the GNU Lesser General Public License (LGPL). Its main goal is to provide an easy-to-use software for modelling, simulating and analyzing processes described by workflow nets, a Petri net class initially introduced by Wil van der Aalst .
WoPeD is a good choice for researchers, teaching staff or students dealing with the application of Petri nets to the area of workflow or business process management. WoPeD has already been successfully used in numerous lectures and student assessment projects all over the world.
Goals and Expected Outcomes. The idea of the project is to extend the tool in order to generally support arc weights (i.e., not just weight 0/1 but any value), which is a mechanism to indicate the number of tokes a transitions requires and produces and thus allows a more detailed behavior. The second contribution, expected by the project is the definition and implementation of a step by step visualization for the creation of the (minimal) coverability graph (e.g., according to ).
- Thomas Freytag, Martin Sänger. WoPeD – An Educational Tool for Workflow Nets. In: Proceedings of the BPM Demo Sessions, Eindhoven, September 2014, pp. 31-35.
- Wil M.P. van der Aaalst. The Application of Petri Nets to Workflow Management. The Journal of Circuits, Systems and Computers, 8(1):21-66, 1998.
- Pierre-Alain Reynier and Frédéric Servais. 2013. Minimal Coverability Set for Petri Nets: Karp and Miller Algorithm with Pruning. Fundamenta Informaticae. 122, 1-2 (January 2013), 1-30.
Extension of PLG with Apromore and Command Line Interface
Introduction. The evaluation of process mining  algorithms requires, as any other data mining task, the availability of large amount of real-world data. Despite the increasing availability of such datasets, they are affected by many limitations, in primis the absence of a “gold standard” (i.e., a reference model). Many times, referring to a gold standard is fundamental in order to evaluate properly the quality of mining algorithms [2, 3]. Several concepts, like precision or recall are actually grounded on this idea. In general, it is possible to identify the concept of gold standard for, basically, all mining tasks.
PLG (Processes and Logs Generator) [4, 5] is a tool, which can be used to generate random business process and is able to simulate them, in order to produce event logs. PLG is based on the generation of process descriptions via a stochastic context-free grammar whose definition is based on well-known process patterns. The process simulation can generate multi-perspective data (i.e., referring not only to the control-flow), different types of noise and is also able to create infinite streams, in order to improve the realism of the whole approach.
Goals and Expected Outcomes. G1. The current version of the PLG tool is capable of generating random process models and import existing ones (as BPMN files generated with Signavio). The first goal is to integrate the tool with Apromore (Advanced Process Model Repository) . Apromore is an open and extensible repository to store and disclose business process models of a variety of types and languages. The expected outcome includes the ability to connect to an Apromore instance and select which processes to import into the current PLG instance (via web-services connections).
G2. The second goal of the thesis consists of creating a Command Line Interface (CLI), which enables the batch execution of several operations including, at least: process generation; process import/export; log and stream generation. The end user should be able to configure the parameters of all these. We expect the ability to provide “scripts” with sequence of instructions to be executed. A possible way of generating such scripts is via the PMLAB tool (i.e., integrating the PLG capabilities into PMLAB). However, if the integration of PLG into this tool is not feasible, a standalone interface could be created as well.
- W. van der Aalst, Process Mining: Discovery, Conformance and Enhancement of Business Processes, Springer Berlin / Heidelberg, 2011.
- K. J. Cios, R. W. Swiniarski, W. Pedrycz and L. A. Kurgan, Data Mining – A Knowledge Discovery Approach, Springer US, 2007.
- C. D. Manning, P. Raghavan and H. Schütze, Introduction to Information Retrieval, Cambridge University Press, 2008.
- A. Burattin and A. Sperduti, “PLG: a Framework for the Generation of Business Process Models and their Execution Logs,” in Proceedings of the 6th International Workshop on Business Process Intelligence (BPI 2010), 2010.
- A. Burattin, “PLG2: Multiperspective Processes Randomization and Simulation for Online and Offline Settings,” CoRR abs/1506.08415, 2015.
- M. La Rosa, H. Reijers, W. van der Aalst, R. Dijkman, J. Mendling, M. Dumas and L. Garcia-Banuelos, “Apromore: An Advanced Process Model Repository,” Expert Systems with Applications, vol. 38, no. 6, 2011.
Privacy Aware Process Mining and Security
Description. Process mining  is a modern technique applied to datasets generated from business processes run in organizations, in order to improve and obtain useful insights and performance measurements on the processes themselves.
While these techniques are very promising in understanding business processes, their complete and efficient implementation inside the organizations is often not possible. Hence, in a way similar to what is done for most non-core activities, and in particular for most ICT services, companies evaluate the possibility of outsourcing such task. However, the confidentiality of the dataset related to the business processes are often key assets for most of modern companies. Then, in order to avoid threats that might come from disclosing such information, most companies decide not to benefit from these process mining techniques.
We would like to study a possible approach toward a complete solution that allows outsource of process mining without thwarting the confidentiality of the dataset and processes. We already analyzed few techniques, in particular in terms of homomorphic encryption . Our early-stage prototype is capable to completely encrypt an event log using AES  (using the Java Security package ) and Paillier cryptosystem  (using a class written from scratch).
Applying Modeling Phase Diagrams to Change Pattern Modeling
Description. Recently, research on factors influencing the quality of business process models has begun to explore another dimension presumably affecting the quality of business process models – the Process of Process Modeling (PPM). The quality of a business process model is presumably highly dependent upon the modeling process that was followed to create it. In this thesis, we will be working on extending previous findings toward a different approach to creating process models. Change Pattern constitute an interesting way of creating process models since the correctness of the resulting process models is guaranteed. Unfortunately, the influence on the modeling process and the demands on the modeler are not understood. For this purpose, Modeling Phase Diagrams will be developed for change pattern modeling to provide researchers with an overview of the modeling process followed. The conducted analysis will help to gain a deeper understanding of the process of process modeling, specifically investigating the impact of utilizing change pattern for creating process models.