Computer Organization And Design 5th Edition Solution Pdf
the conventional software development involves a number of well-defined phases: requirement analysis, design, implementation, tests, maintenance, and evolution. all these phases have an influence on software quality, since they are considered important stages of the development process. the uml helps to document the software design at different levels. however, the model does not provide a tool to automatically measure and analyze how good is the design based on a set of requirements. this chapter shows how to use a top-down approach to assess the quality of the design based on the requirements. the model can be used to: (a) assess the quality of the requirements and (b) measure the quality of the design. this chapter presents a top-down approach to measure design quality and provides tools to analyze the design of the software on the basis of these measures. the approach aims at automatically capturing the quality aspects of the design and performs a good trade-off between the quality attributes under analysis.
the ideal aim of decision support systems is to assist decision making. data mining is a powerful technique for data analysis in decision support systems, which may help decision makers, managers, and other stakeholders to better understand the problem in which they are working. however, the patterns in data have been discovered by different researchers in many domains. in this work, we have investigated the possibilities of using the competitive analysis method to discover potential patterns that may be useful in a data mining process. we used three well-known data sets generated with a binomial distribution to demonstrate that the common competitive analysis approach is based on probabilistic reasoning and can be successfully applied to work out useful patterns in data. we have proved that the data set generated with a normal distribution is not suitable to application of the competitive analysis method in data mining. in the same way, we have compared two data sets generated using a binomial distribution and one generated using a normal distribution. we have shown that the data set generated with a binomial distribution may be more suitable to application of the competitive analysis method in data mining.
we have applied the evaluation criteria described above to evaluate the relative lexicographic success score (rls) method proposed in [ 25 ]. all criteria defined in this paper were considered and the rls method was compared with the ranking method proposed by arantes et al. [ 26 ]. to do this, we have used data sets generated by a binomial distribution. we also present the comparative study of three data sets which are generated with different criteria, i.e., the uncertainty data set and the numerical data sets generated by the random seed as defined in [ 23 ]. we have shown that the rls method can be successfully applied to work out a ranking based on the evaluation criteria described in this paper, which is more effective than the ranking algorithm proposed by arantes et al.[[ 26 ] however, it could be possible to implement the evaluations using the ranking algorithm for experiment analysis. in fact, when the evaluation criteria are applied to a data set that is generated with the same criteria, the ranking algorithm proposed by arantes et al. is more effective. with respect to the data sets generated by the random seed, the ranking algorithm proposed by arantes et al.
as the industry turned to becoming more of a service-oriented architecture, ibm’s product portfolio expanded to include both client and server technologies. originally introduced for the ibm personal computer in 1978, the system/38 client workstation was the first client machine designed to use the client-server paradigm. it is both a client and a server, able to send requests to other system/38 systems, but being able to run programs for its own user and to display its work. the name is an acronym which refers to the overall concept of the client-server model.