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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.
Nonfunctional requirements, software risk, software performance, UML, performance failure, Functional Failure Analysis.
Rania Elnaggar, Hany H. Ammar, Walid Abdelmoez, Ahmed Hassan, Kalaivani Appukkutty, Vittorio Cortellessa, Ajith R. Guedem, Katerina Goseva-Popstojanova, "Model-Based Performance Risk Analysis", IEEE Transactions on Software Engineering, vol. 31, no. , pp. 3-20, January 2005, doi:10.1109/TSE.2005.12
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