Performance Trees : A Query Specification Formalism For Quantitative Performance Analysis

Real-life systems are often plagued by unanticipated perfor mance problems caused by subtle bugs and bottlenecks. It is thus essential for system d signers and engineers to have an understanding of their fundamental performance cha ra teristics, both before and after implementation. Stochastic modelling and analysis r espectively provide the means to abstract systems as mathematical descriptions and to der ive quantifiable measures of interest from them. A major, and so far largely unaddressed, challenge is the spe cification of complex performance queries on models in an accessible manner that does not sacrifice expressiveness. This thesis attempts to address this challenge by intr oducing Performance Trees, a new formalism for the graphical specification of complex pe rformance queries on stochastic models. Performance Trees are designed to be access ible by providing a more intuitive approach to query specification, expressive by be ing able to reason about a far broader range of concepts than current alternatives, exten sibl by supporting additional user-defined concepts, and versatile through their applica bility to multiple modelling formalisms. Performance Trees are presented in the context of a rigorous formal framework that defines the syntax, typing and quantitative semantics o f operators. Prototype tool support is implemented in the form of a module of thePIPE2Petri net tool, which provides graphical user interfacing and Performance Tre query design capabilities. Query evaluation is supported by a set of integrated paralle l and distributed analysis tools, and realised by the distribution of computations onto a dedi cated Grid cluster. The practical application of Performance Trees is demonstr ated in the context of case study analysis scenarios of an electronic voting system, an onli e transaction system and a hospital’s Accident & Emergency unit.