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e-Book Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness (Lecture Notes in Business Information Processing) epub download

e-Book Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness (Lecture Notes in Business Information Processing) epub download

Author: Jan Mendling
ISBN: 3540892230
Pages: 194 pages
Publisher: Springer; 2008 edition (November 21, 2008)
Language: English
Category: Programming
Size ePUB: 1967 kb
Size Fb2: 1115 kb
Size DJVU: 1290 kb
Rating: 4.7
Votes: 244
Format: lrf lrf docx lrf
Subcategory: Technologies

e-Book Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness (Lecture Notes in Business Information Processing) epub download

by Jan Mendling



Business process modeling plays an important role in the management of business processes.

Business process modeling plays an important role in the management of business processes. 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. Contact us. Terms and Conditions.

Published in Lecture Notes in Business Information Processing 2008 As valuable design artifacts, business process models are subject t. .

Published in Lecture Notes in Business Information Processing 2008. 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 Mendlingdevelops a framework for the detection of formal errors in business process models and the prediction of error probability based on quality attributes of these model. ONTINUE READING.

Metrics for Process Models book. Start by marking Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness as Want to Read: Want to Read savin. ant to Read. Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness.

Электронная книга "Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness", Jan Mendling. Эту книгу можно прочитать в Google Play Книгах на компьютере, а также на устройствах Android и iOS. Выделяйте текст, добавляйте закладки и делайте заметки, скачав книгу "Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness" для чтения в офлайн-режиме.

A recent study by Mendling et al. explores in how far certain complexity metrics of business process models have the potential to serve as error determinants.

from book Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness. Metrics for Business Process Models. Chapter · with 531 Reads. A recent study by Mendling et al. The authors conclude that complexity indeed appears to have an impact on error probability. Before we can test such a hypothesis in a more general setting, we have to establish an understanding of how we can define determinants that drive error probability and how we can measure them.

I made it for authors like me; who barely sold any books, but it still felt good to know that someone found your writing valuable. It grew to be valuable to so many others

I made it for authors like me; who barely sold any books, but it still felt good to know that someone found your writing valuable. It grew to be valuable to so many others. I'm sorry this has happened and I have to now focus on my new wife (married for the 1st time Aug 3rd) and what my future can be now that my income is gone. Regretfully, Mario Lurig Founder, Developer, Advocate: NovelRank. PS If you found this free service useful in the last 9 years, please consider supporting me directly: Donate.

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Metrics for Process Models: Empirical Foundations of Verification, Error Prediction, and Guidelines for Correctness (Lecture Notes in Business Information Processing). 4 Mb. Business Process Management: 8th International Conference, BPM 2010, Hoboken, NJ, USA, September 13-16, 2010, Proceedings (Lecture Notes in Computer. Internet Web, and HCI). Richard Hull, Jan Mendling, Stefan Tai. Category: Компьютеры.

KEYWORDS: Business Process vering, Business Process Requirements Engineering, BPMN MIWG, As-Is Business Process Creation, Model Semantics, Model Refinement, LORS Framework. JOURNAL NAME: Journal of Software Engineering and Applications, Vo. 0 N., February 7, 2017. ABSTRACT: In recent years, the process orientation requirements engineering field has received significant interest.

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.