Abstract-Risk assessment is an essential part in managing software development. Performing risk assessment during the early development phases enhances resource allocation decisions. In order to improve the software development process and the quality of software products, we need to be able to build risk analysis models based on data that can be collected early in the development process. These models will help identify the high-risk components and connectors of the product architecture, so that remedial actions may be taken in order to control and optimize the development process and improve the quality of the product. In this paper, we present a risk assessment methodology which can be used in the early phases of the software life cycle. We use the Unified Modeling Language (UML) and commercial modeling environment Rational Rose Real Time (RoseRT) to obtain UML model statistics. First, for each component and connector in software architecture, a dynamic heuristic risk factor is obtained and severity is assessed based on hazard analysis. Then, a Markov model is constructed to obtain scenarios risk factors. The risk factors of use cases and the overall system risk factor are estimated using the scenarios risk factors. Within our methodology, we also identify critical components and connectors that would require careful analysis, design, implementation, and more testing effort. The risk assessment methodology is applied on a pacemaker case study.

Introduction-The human multi-drug resistance gene (MDR1, ABCB1) codes for P-glycoprotein (P-gp), an important membrane-bound efflux transporter known to confer anti-cancer drug resistance as well as affect the pharmacokinetics of many drugs and xenobiotics. A number of single nucleotide polymorphisms (SNPs) have been identified throughout the ABCB1 gene which may have an effect on P-gp expression levels and function. Haplotype as well as genotype analysis of SNPs is becoming increasingly important in identifying genetic variants underlying susceptibility to human disease. Three SNPs, 1236C>T, 2677G>T, and 3435C>T have been repeatedly shown to predict changes in the function of P-gp. The frequencies with which these polymorphisms exist in a population have also been shown to be ethnically related.

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