Theoretical and practical complexity of unified modeling language: Delphi study and metrics analyses

• Main Authors: ERICKSON, J., SIAU, Keng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: UML; complexity; complexity metrics; Delphi study; modeling method metrics; Databases and Information Systems; Programming Languages and Compilers
• Online Access: https://ink.library.smu.edu.sg/sis_research/9646; https://ink.library.smu.edu.sg/context/sis_research/article/10646/viewcontent/Theoretical_and_Practical_Complexity_of_Unified_Modeling_Language__Delphi_Study_and_Metrics_Analyses.pdf
• Institution: Singapore Management University

Systems have become increasingly complex, and as a result development methods have become more complex as well. The unified modeling language (UML) has been criticized for the often cited and sometimes over- whelming complexity it presents to its users, and those seeking to learn to use it. Using Rossi and Brinkkemper’s (1996) complexity metrics, Siau and Cao (2001) completed a complexity analysis of UML and 36 other modeling techniques, finding that UML is indeed more complex than other techniques. Siau, Erickson and Lee (2002) proposed that Rossi and Brinkkemper’s metrics present the theoretical maximum complexity, known as theoretical complexity. This is different from a practice-based complexity, known as practical complexity, that more accurately reflects the complexity of the language in practice. This research develops a subset of UML (a kernel) composed of the most commonly used constructs, that can be equated with the complexity that practitioners actually face when using the modeling language. A Delphi study is conducted using UML experts in identifying a use-based UML kernel. Metric analyses are then computed and analyzed.