00454nas a2200133   4500008004100000245004600041210004100087100002300128700002300151700002700174700002400201700002000225856007500245       2018                        eng d00aIs this Sentence Difficult? Do you Agree?0 athis Sentence Difficult Do you Agree1 aBrunato, Dominique1 aDe Mattei, Lorenzo1 aDell’Orletta, Felice1 aIavarone, Benedetta1 aVenturi, Giulia  uhttps://datasciencephd.eu/publications/sentence-difficult-do-you-agree01713nas a2200121   4500008004100000245009400041210006900135520126200204100002701466700002201493700002101515856005501536       2017                        eng d00aA Tool for Aligning Event Logs and Prescriptive Process Models through Automated Planning0 aTool for Aligning Event Logs and Prescriptive Process Models thr3 aIn Conformance Checking, alignment is the problem of detecting and repairing nonconformity between the actual execution of a business process, as recorded in an event log, and the model of the same process. Literature proposes solutions for the alignment problem that are implementations of planning algorithms built ad-hoc for the specific problem. Unfortunately, in the era of big data, these ad-hoc implementations do not scale sufficiently compared with well-established planning systems. In this paper, we tackle the above issue by presenting a tool, also available in ProM, to represent instances of the alignment problem as automated planning problems in PDDL (Planning Domain Definition Language) for which state-of-the-art planners can find a correct solution in a finite amount of time. If alignment problems are converted into planning problems, one can seamlessly update to the recent versions of the best performing automated planners, with advantages in term of versatility and customization. Furthermore, by employing several processes and event logs of different sizes, we show how our tool outperforms existing approaches of several order of magnitude and, in certain cases, carries out the task while existing approaches run out of memory.1 ade Leoni, Massimiliano1 aLanciano, Giacomo1 aMarrella, Andrea  uhttp://ceur-ws.org/Vol-1920/BPM_2017_paper_187.pdf