Научно-исследовательский семинар "Программная инженерия: управление разработкой"-2
- To learn the fundamental principles of process mining and its main components: process discovery, conformance checking and enhancement
- To study process mining algorithms and approaches
- To gain practical experience in the critical discussion of scientific papers
- Students will know the basic principles of process discovery, conformance checking and process mining constituting the area process mining.
- Students will learn the most wide-spread algorithms, which support the automated process discovery.
- Students will learn the most wide-spread algorithms, which support the automated check of the conformance between a discovered process model and an event log.
- Students will gain the experience of making reports covering the main contributions of research articles.
- Students will gain the experience of reviewing and analyzing reports made by others.
- Process Mining: EssentialsEvent Logs: traces, actions, attributes, timestamps. Discovering process models from event logs: algorithms, approaches. Conformance checking between discovered models and event logs: fitness, precision, and generalization. Enhancement of process models: repair of process models.
- Process Mining in Software EngineeringAnalyzing (stack) traces of software: architecture, bottlenecks, identification of subprograms, interactions between components of a program. Analyzing patterns and anti-patterns in program behavior: cancellations, exceptional behaviors. Using process mining is specific application areas through the lens of software engineering: healthcare, education, banking, insurance etc.
- Interim assessment (2 module)The final mark for the research seminar Ofinal is evaluated by the following formula: Ofinal = 0,6 * Oreport + 0,4 * Oreport + Oextra - Oskipped, where Oextra assesses the amount of extra work as a speaker/reviewer; additional experiments with software tools; analysis of the practical application, further works on the topic; active participation in the discussion (especially, without being a «compulsory» reviewer). Oskipped depends on the number of skipped classes (at most, 2 classes can be skipped without influencing the final mark): Oskipped = (# of skipped classes - 2) / 4, i.e., i.e., every skipped class (more than two) will subtract 0.25 from the final mark for the research seminar.
- Aalst, W. van der. (2016). Process Mining : Data Science in Action (Vol. Second edition). Heidelberg: Springer. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=1203872
- Josep Carmona, Boudewijn van Dongen, Andreas Solti, & Matthias Weidlich. (2018). Conformance Checking : Relating Processes and Models (Vol. 1st ed. 2018). Springer.
- Eric Badouel, Luca Bernardinello, & Philippe Darondeau. (2015). Petri Net Synthesis (Vol. 1st ed. 2015). Springer.
- Wolfgang Reisig. (2013). Understanding Petri Nets : Modeling Techniques, Analysis Methods, Case Studies (Vol. 2013). Springer.