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Metrics for Process Models [electronic resource] :Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness / by Jan Mendling.

by Mendling, Jan [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Business Information Processing: 6Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2008.Description: online resource.ISBN: 9783540892243.Subject(s): Computer science | Software engineering | Information systems | Management information systems | Computer Science | Information Systems Applications (incl.Internet) | Business Information Systems | Computer Appl. in Administrative Data Processing | Software EngineeringDDC classification: 005.7 Online resources: Click here to access online
Contents:
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.
In: Springer eBooksSummary: 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.
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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.

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.

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