Doctoral defence: Kristo Raun "Adaptive out-of-order handling in streaming conformance checking“.

On 25 November at 12:15 Kristo Raun will defend his thesis "Adaptive out-of-order handling in streaming conformance checking“ to obtain the degree of Doctor of Philosophy (in Computer Science).  

Supervisors
Visiting Professor Riccardo Tommasini, University of Tartu
Associate Professor Ahmed Awad, The British University in Dubai (United Arab Emirates)

Opponents 
Professor Han van der Aa, University of Vienna (Austria) 
Associate Professor  Marwan Hassani, Eindhoven University of Technology (Netherlands)

Summary
The occurrence of errors in business processes can have a wide impact on the organization. Thus, it is important to find deviations in a fast, accurate, and explainable manner. The state-of-the-art approach for finding deviations via conformance checking is an alignment, showing how the real-life activities match the process. Unfortunately, finding the alignment using current methods is computationally slow and impractical for fast-arriving data. The first part of the thesis introduces a trie-based conformance checking approach that is computationally more effective than previous methods with a small impact on accuracy. 

The longer it takes from the occurrence of a discrepancy until it is discovered, the bigger its potential impact. Streaming data, i.e., data that arrives in near real-time, is important as it allows conformance checking to take place close to the actual occurrence of events. The second contribution presents an algorithm that works on streaming data, outputs an alignment, and is, in some experiments, several orders of magnitude faster than the previous state of the art. 

Analyzing streaming data is complex, as the data arrives continuously, and the stream is theoretically infinite. The third contribution analyzes how to improve the algorithm so that we could assess the completeness of a case in a business process and the confidence of the case concluding. 

Fast-paced and distributed data streams can cause out-of-order event arrival. That is, an event that occurred later arrives in the system before another event that occurred earlier. In the final contribution, a novel method is introduced for handling out-of-order event arrival, being knowingly the first method to tackle this problem in conformance checking. The method is adaptable, regulating itself based on the level of out-of-orderedness in the stream. 

In this summary, the topics of the title were discussed out of order, but hopefully, it was possible to adapt to this during the reading process.