Software reliability, one of the major software quality attributes, quantitatively expresses the continuity of correct service delivery. In current practice, reliability models are typically measurement-based models, and mostly employed in isolation at the later stage of the soft ware development process, after architectural decisions have been made that cannot easily be reversed early software reliability prediction models are often insufficiently formal to be ana- lyzable and not usually connected to the target system. We postulate it is possible to overcome these issues by supporting software reliability engineering from requirements to deployment using scenario specifications. We contribute a novel reliability prediction technique that takes into account the component structure exhibited in the scenarios and the concurrent nature of component-based systems by extending scenario specifications to model (1) the probability of component failure, and (2) scenario transition probabilities. Those scenarios are subsequently transformed into enhanced behaviour models to compute the system reliability. Additionally we enable the integration between reliability and development models through profiles that extend the core Unified Modelling Language (UML). By means of a reli ability profile, the architecture of a component-based system can express both method invoca tions and deployment relationships between the application components in one environment. To facilitate reliability prediction, and determine the impact of concurrency on systems reliability, we have extended the Label Transition System Analyser Tool (LTSA), implementing a plugin for reliability analysis. Finally, we evaluate our analysis technique with a case study focusing on Condor, a dis tributed job scheduler and resource management system. The purpose of the case study is to evaluate the efficacy of our analysis technique and to compare it with other reliability tech niques
