AIMar 13, 2025

DeclareAligner: A Leap Towards Efficient Optimal Alignments for Declarative Process Model Conformance Checking

arXiv:2503.10479v11 citationsh-index: 27Eng appl artif intell
Originality Incremental advance
AI Analysis

This addresses efficiency and scalability issues in process conformance checking for engineering applications, enabling better process improvement, though it appears incremental as it builds on existing AI techniques like A* search.

The paper tackles the computational challenge of computing optimal alignments for declarative process model conformance checking by introducing DeclareAligner, which significantly outperforms the state of the art on 8,054 synthetic and real-life alignment problems.

In many engineering applications, processes must be followed precisely, making conformance checking between event logs and declarative process models crucial for ensuring adherence to desired behaviors. This is a critical area where Artificial Intelligence (AI) plays a pivotal role in driving effective process improvement. However, computing optimal alignments poses significant computational challenges due to the vast search space inherent in these models. Consequently, existing approaches often struggle with scalability and efficiency, limiting their applicability in real-world settings. This paper introduces DeclareAligner, a novel algorithm that uses the A* search algorithm, an established AI pathfinding technique, to tackle the problem from a fresh perspective leveraging the flexibility of declarative models. Key features of DeclareAligner include only performing actions that actively contribute to fixing constraint violations, utilizing a tailored heuristic to navigate towards optimal solutions, and employing early pruning to eliminate unproductive branches, while also streamlining the process through preprocessing and consolidating multiple fixes into unified actions. The proposed method is evaluated using 8,054 synthetic and real-life alignment problems, demonstrating its ability to efficiently compute optimal alignments by significantly outperforming the current state of the art. By enabling process analysts to more effectively identify and understand conformance issues, DeclareAligner has the potential to drive meaningful process improvement and management.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

Your Notes