State dependence in performance evaluation of component-based software systems

Abstract

Integrating rising variability of software systems in performance prediction models is crucial to allow widespread industrial use of performance prediction. One of such variabilities is the dependency of system performance on the context and history-dependent internal state of the system (or its components). The questions that rise for current prediction models are (i) how to include the state properties in a prediction model, and (ii) how to balance the expressiveness and complexity of created models.Only a few performance prediction approaches deal with modelling states in component-based systems. Currently, there is neither a consensus in the definition, nor in the method to include the state in prediction models. For these reasons, we have conducted a state-of-the-art survey of existing approaches addressing their expressiveness to model stateful components. Based on the results, we introduce a classification scheme and present the state-defining and state-dependent model parameters. We extend the Palladio Component Model (PCM), a model-based performance prediction approach, with state-modelling capabilities, and study the performance impact of modelled state. A practical influences of the internal state on software performance is evaluated on a realistic case study.

Towards Readability Aspects of Probabilistic Mode Automata

“…Several component-based prediction approaches, e.g. Palladio [23,30,6], CB-SPE [7], ROBOCOP [8] (see also a survey in [5]) derive the benefits of reusing well-documented component specifications. In our approach we focus on the questions of resourceawareness and adaptivity of systems as well as on the readability aspects of the formalism.…”

Reconciling a Component and Process View

“…Several component-based prediction approaches, e.g. Palladio [8], CB-SPE [9], ROBO-COP [10] derive the benefits of reusing well-documented component specifications (cf. also a survey in [11]).…”

Stateful component-based performance models

“…As a proof of the concept, we extended an existing performance prediction framework and employed it in a realworld case study, demonstrating the effect of state modelling on software performance. The paper is an extension of our previous work [16] with an expanded state-effect analysis, an extensive experimental evaluation of newly derived heuristics, and an additional case study.…”

“…Along the scope dimension, it distinguishes component-, system-and user-specific states, all defined below. With respect to the time dimension, we examined all the stages of componentbased system life cycle [16], and observed that a state is by nature a dynamic information that evolves independently for individual elements in the system. If it is fixed along life cycle, it is not set before the element gains its identity (instantiation stage in case of a component, assembly stage in case of a system).…”