Francesco Chiariello

Université de Toulouse

Answer Set Programming (ASP), a well-known declarative logic programming paradigm, has recently found practical application in Process Mining. In particular, ASP has been used to model tasks involving declarative specifications of business processes. In this area, Declare stands out as the most widely adopted declarative process modeling language,...

In this work, we present a novel approach to learning Linear Temporal Logic (LTL) formulae from event logs by leveraging statistical techniques from sequential analysis. In particular, we employ the Sequential Probability Ratio Test (SPRT), using Trace Alignment to quantify the discrepancy between a trace and a candidate LTL formula. We then test t...

Answer Set Programming (ASP), a well-known declarative programming paradigm, has recently found practical application in Process Mining, particularly in tasks involving declarative specifications of business processes. Declare is the most popular declarative process modeling language. It provides a way to model processes by sets of constraints, exp...

We present a new approach for solving temporal problems using Answer Set Programming (ASP), which exploits the automata representation of temporal specifications. This approach is then used to solve key problems from Process Mining. The contributions of the paper are manifold. Firstly, for the Temporal Logics community, it provides a tool to perfor...

Linear Temporal Logic on process traces (or LTL) is a logic introduced to specify and reason over the temporal properties of (the traces generated by) business processes. So far, its relation with finite-state automata has not been explored and researchers resorted to more expressive logics and the corresponding automata construction algorithms. In...

This thesis investigates the use of finite-state automata for various process-related tasks. Automata are a possible choice for a process modeling language that has gained increasing attention in recent years. The main reason for this is their relation to temporal logics, which makes automata easy to define and understand, while preserving all the...

We present a tool for compiling three problems from the Process Mining community into Answer Set Programming: Log Generation, Conformance Checking, and Query Checking. For each problem, two versions are addressed, one considering only the control-flow perspective and the other considering also the data perspective. The tool can support companies in...

We put forward Answer Set Programming (ASP) as a solution approach for three classical problems in Declarative Process Mining: Log Generation, Query Checking, and Conformance Checking. These problems correspond to different ways of analyzing business processes under execution, starting from sequences of recorded events, a.k.a. event logs. We tackle...