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Lecture Notes in Computer Science
Motivated by the problem of detecting software performance anti-patterns in data-intensive applications (DIAs), we present a tool, Tulsa, for transforming software architecture models specified through UML into Layered Queueing Networks (LQNs), which are analytical performance models used to capture contention across multiple software layers. In particular, we generalize an existing transformation based on the Epsilon framework to generate LQNs from UML models annotated with the DICE profile,doi:10.1007/978-3-319-66335-7_18 fatcat:2ssm5xoyerdujjim3esvpqvxl4