MINERful is a fast process mining tool for discovering declarative process models out of event logs. Event logs can be either real or synthetic, stored as XES, MXML, or text files (a collection of strings, in which every character is considered as an event, every line as a trace). Among the other things, MINERful can also create synthetic logs and export them as XES or MXML files, simplify existing Declare models, and import/export models written in JSON or in the ConDec native language. Simply play around with it!
For updated info on the installation, usage, etc., please refer to the Wiki!
Publications and further material
Selected publications about MINERful and presentation slides:
The main discovery algorithm:
Claudio Di Ciccio, Massimo Mecella: On the Discovery of Declarative Control Flows for Artful Processes. ACM Trans. Management Inf. Syst. 5(4): 24:1-24:37 (2015)
Discovery of target-branched (read: more complex) declarative models:
Claudio Di Ciccio, Fabrizio Maria Maggi, Jan Mendling: Efficient discovery of Target-Branched Declare constraints. Inf. Syst. 56: 258-283 (2016)
Getting rid of redundancies and inconsistencies:
Claudio Di Ciccio, Fabrizio Maria Maggi, Marco Montali, Jan Mendling: Resolving inconsistencies and redundancies in declarative process models. Inf. Syst. 64: 425-446 (2017)
Retaining only non-vacuously satisfied (read: relevant) constraints:
Claudio Di Ciccio, Fabrizio Maria Maggi, Marco Montali, Jan Mendling: On the relevance of a business constraint to an event log. Inf. Syst. 78: 144-161 (2018)
Simulation of declarative models:
Claudio Di Ciccio, Mario Luca Bernardi, Marta Cimitile, Fabrizio Maria Maggi: Generating Event Logs Through the Simulation of Declare Models. EOMAS@CAiSE 2015: 20-36
Please read the LICENSE file.