Paper Info
Title
Metrics for evaluation of metaprogram complexity
Abstract
The concept of complexity is used in many areas of computer science and software engineering. Software complexity metrics can be used to evaluate and compare quality of software development and maintenance processes and their products. Complexity management and measurement is especially important in novel programming technologies and paradigms, such as aspect-oriented programming, generative programming, and metaprogramming, where complex multi-language and multi-aspect program specifications are developed and used. This paper analyzes complexity management and measurement techniques, and proposes five complexity metrics (Relative Kolmogorov Complexity, Metalanguage Richness, Cyclomatic Complexity, Normalized Difficulty, Cognitive Difficulty) for measuring complexity of metaprograms at information, metalanguage, graph, algorithm, and cognitive dimensions.
Year
DOI
Venue
2010
10.2298/CSIS090315004D
COMPUTER SCIENCE AND INFORMATION SYSTEMS
Keywords
Field
DocType
Metaprogramming,complexity evaluation,metaprogram metric
Metaprogramming,Kolmogorov complexity,Computer science,Cyclomatic complexity,Theoretical computer science,Descriptive complexity theory,Metalanguage,Complexity management,Worst-case complexity,Software development
Journal
Volume
Issue
ISSN
7
4
1820-0214
Citations 
PageRank 
References 
5
0.48
11
Authors
2
Name
Order
Citations
PageRank
Robertas Damasevicius128162.75
Vytautas Stuikys210217.07