TY - BOOK AU - ED - SpringerLink (Online service) TI - Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness T2 - Lecture Notes in Business Information Processing, SN - 9783540892243 AV - QA76.76.A65 U1 - 005.7 23 PY - 2008/// CY - Berlin, Heidelberg PB - Springer Berlin Heidelberg KW - Computer science KW - Software engineering KW - Information systems KW - Management information systems KW - Computer Science KW - Information Systems Applications (incl.Internet) KW - Business Information Systems KW - Computer Appl. in Administrative Data Processing KW - Software Engineering N1 - Business Process Management -- Event-Driven Process Chains (EPC) -- Verification of EPC Soundness -- Metrics for Business Process Models -- Validation of Metrics as Error Predictors -- Implications for Business Process Modeling; ZDB-2-SCS N2 - Business process modeling plays an important role in the management of business processes. As valuable design artifacts, business process models are subject to quality considerations. The absence of formal errors such as deadlocks is of paramount importance for the subsequent implementation of the process. In his book Jan Mendling develops a framework for the detection of formal errors in business process models and the prediction of error probability based on quality attributes of these models (metrics). He presents a precise description of Event-driven Process Chains (EPCs), their control-flow semantics and a suitable correctness criterion called EPC soundness UR - http://dx.doi.org/10.1007/978-3-540-89224-3 ER -