Abstract-Performance is a nonfunctional software attribute that plays a crucial role in wide application domains spreading from safety-critical systems to e-commerce applications. Software risk can be quantified as a combination of the probability that a software system may fail and the severity of the damages caused by the failure. In this paper, we devise a methodology for estimation of performance-based risk factor, which originates from violations of performance requirements (namely, performance failures). The methodology elaborates annotated UML diagrams to estimate the performance failure probability and combines it with the failure severity estimate which is obtained using the Functional Failure Analysis. We are thus able to determine risky scenarios as well as risky software components, and the analysis feedback can be used to improve the software design. We illustrate the methodology on an e-commerce case study using step-by-step approach and then provide a brief description of a case study based on large real system.
Software Risk Assessment based on UML models Kalaivani Appukkutty Risk is the possibility of suffering loss. Risks identified during the early stages of software development are easier and cheaper to handle by making changes to the software architecture. This thesis presents methodologies to assess software risk using Unified Modeling Language (UML) specifications of the software from the early design stages. We present methodologies to assess two types of software risk: Requirementsbased risk and Performance-based risk. In assessing requirements-based risk, each requirement is mapped to a specific operational scenario in UML. The risk factor of a scenario in a failure mode is obtained by combining the probability of failure of the scenario and the severity of the failure. For the performance-based risk analysis, we use UML diagrams with performance related annotations, build a software execution model for each scenario and then map it to a system execution model using the deployment information. For estimating the performance-based failures of each scenario we use an asymptotic bounding analysis. The methodologies are applied on various case studies.
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