Publication Type
Journal Article
Version
publishedVersion
Publication Date
8-2007
Abstract
The estimation of theoretical and practical complexity of a system development method is discussed. Executable model capability allow developers to transform models developed during the Systems Analysis and Design portion of the systems development process into working applications. Systems are becoming more complex mostly because of influencing factors such as required and enhanced functionality, interoperability, and security. Other trends that impact the complexity of applications include systems such as enterprise resource planning, supply chain management, and customer relationship management. These types of systems are very large and complex and require close internal cooperation for the implementing organizations individually and also external cooperation and connection to their business partners up and down the supply chain. A realistic estimation of the complexity of a modeling language can also provide better ways of learning and using various development methods.
Keywords
Customer relationship management, Internal organization cooperation, Realistic estimation, System development methods
Discipline
Databases and Information Systems | Numerical Analysis and Scientific Computing
Research Areas
Data Science and Engineering; Information Systems and Management
Areas of Excellence
Digital transformation
Publication
Communications of the ACM
Volume
50
Issue
8
First Page
46
Last Page
51
ISSN
0001-0782
Identifier
10.1145/1278201.1278205
Publisher
Association for Computing Machinery (ACM)
Citation
ERICKSON, John and SIAU, Keng.
Theoretical and practical complexity of modeling methods. (2007). Communications of the ACM. 50, (8), 46-51.
Available at: https://ink.library.smu.edu.sg/sis_research/9585
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1145/1278201.1278205
Included in
Databases and Information Systems Commons, Numerical Analysis and Scientific Computing Commons