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  -