Abstract
This paper describes the tool CASPA, a new performance evaluation tool which is based on a Markovian stochastic process algebra. CASPA uses multi-terminal binary decision diagrams (MTBDD) to represent the labelled continuous time Markov chain (CTMC) underlying a given process algebraic specification. All phases of modelling, from model construction to numerical analysis and measure computation, are based entirely on this symbolic data structure. We present several case studies which demonstrate the superiority of CASPA over sparse-matrixbased process algebra tools. Furthermore, CASPA is compared to other symbolic modelling tools. © Springer-Verlag 2004.
Cite
CITATION STYLE
Kuntz, M., Siegle, M., & Werner, E. (2004). Symbolic performance and dependability evaluation with the tool CASPA. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3236, 293–307. https://doi.org/10.1007/978-3-540-30233-9_22
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
