Techniques for a Posteriori Analysis of Declarative Processes

Abstract

The increasing availability of event data recorded by information systems, electronic devices, web services and sensor networks provides detailed information about the actual processes in systems and organizations. Process mining techniques can use such event data to discover processes and check the conformance of process models. For conformance checking, we need to analyze whether the observed behavior matches the modeled behavior. In such settings, it is often desirable to specify the expected behavior in terms of a declarative process model rather than of a detailed procedural model. However, declarative models do not have an explicit notion of state, thus making it more difficult to pinpoint deviations and to explain and quantify discrepancies. This paper focuses on providing high-quality and understandable diagnostics. The notion of activation plays a key role in determining the effect of individual events on a given constraint. Using this notion, we are able to show cause-and-effect relations and measure the healthiness of the process

Conformance checking based on multi-perspective declarative process models

“…In this case, we say that the constraint is vacuously satisfied [35]. In [18], the authors introduce the notion of behavioral vacuity detection according to which a constraint is non-vacuously satisfied in a trace when it is activated in that trace. An activation of a constraint in a trace is an event whose occurrence imposes, because of that constraint, some obligations on other events (targets) in the same trace.…”

“…In trace t 4 , for example, the response constraint G(a → Fb) is activated twice, but the first activation leads to a fulfillment (eventually b occurs) and the second activation leads to a violation (b does not occur subsequently). An algorithm to discriminate between fulfillments and violations for a constraint in a trace is presented in [18]. Table 1 reports the activations for the main Declare templates.…”

“…In [18], the authors report an approach that can be used to evaluate the conformance of a log with respect to a Declare model. In particular, their algorithms compute, for each trace, whether a Declare constraint is violated or fulfilled.…”

“…Table 1 reports the activations for the main Declare templates. In [18], the authors define two metrics to measure the conformance of an event log with respect to a constraint in terms of violations and fulfillments, called violation ratio and fulfillment ratio of the constraint in the log. These metrics are valued 0 if the log contains no activations of the considered constraint.…”

“…Conformance checking approaches based on the control-flow perspective have been defined for declarative models as well (e.g. [16,17,18]). More recently the additional data perspective has been considered in [19,20], even if in these works the data perspective is not fully integrated with the control flow perspective.…”