Efficient Checking of Temporal Compliance Rules Over Business Process Event Logs
This work addresses the need for interactive compliance monitoring in business processes, offering an incremental improvement over existing full-scan methods.
The paper tackles the problem of efficiently verifying temporal compliance rules over large business process event logs by proposing a data structure that enables sublinear-time evaluation, achieving real-time checking on twenty real-life logs.
Verifying temporal compliance rules, such as a rule stating that an inquiry must be answered within a time limit, is a recurrent operation in the realm of business process compliance. In this setting, a typical use case is one where a manager seeks to retrieve all cases where a temporal rule is violated, given an event log recording the execution of a process over a time period. Existing approaches for checking temporal rules require a full scan of the log. Such approaches are unsuitable for interactive use when the log is large and the set of compliance rules is evolving. This paper proposes an approach to evaluate temporal compliance rules in sublinear time by pre-computing a data structure that summarizes the temporal relations between activities in a log. The approach caters for a wide range of temporal compliance patterns and supports incremental updates. Our evaluation on twenty real-life logs shows that our data structure allows for real-time checking of a large set of compliance rules.