Performance evaluation of enterprise architecture using fuzzy sequence diagram

Developing an Enterprise Architecture is a complex task and to control the complexity of the regulatory framework we need to measure the relative performance of one system against other available systems. On the other hand, enterprise architecture cannot be organized without the use of a logical structure. The framework provides a logical structure for classifying architectural output. Among the common architectural framework, the C4ISR framework and methodology of the product is one of the most popular techniques. In this paper, given the existing uncertainties in system development and information systems, a new version of UML called Fuzzy-UML is proposed for enterprise architecture development based on fuzzy Petri nets. In addition, the performance of the system is also evaluated based on Fuzzy sequence diagram

Performance evaluation of enterprise architecture with a formal fuzzy model (FPN)

Preparing enterprise architecture is complicated procedure, which uses framework as structure regularity and style as the behavior director for controlling complexity. As in architecture behavior, precedence over structure, for better diagnosis of a behavior than other behaviors, there is a need to evaluate the architecture performance. Enterprise architecture cannot be organized without the benefit of the logical structure. Framework provides a logical structure for classifying architectural output. Among the common architectural framework, the C4ISR is one of the most appropriate frameworks because of the methodology of its production and the level of aggregation capability and minor revisions. C4ISR framework, in three views and by using some documents called product, describes the architecture. In this paper, for developing the systems, there are always uncertainties in information systems and we may use new version of UML called FUZZY-UML, which includes structure and behavior of the system. The proposed model of this paper also uses Fuzzy Petri nets to analyze the developed system

Evaluation of software architecture using fuzzy colored Petri nets

Software Architecture (SA) is one of the most important artifacts for life cycle of a software system because it incorporates some important decisions and principles for the system development. On the other hand, developing the systems based on uncertain and ambiguous requirement has been increased, significantly. Therefore, there have been significant attentions on SA requirements. In this paper, we present a new method for evaluation of performance characteristics based on a use case, response time, and queue length of SA. Since there are some ambiguities associated with considered systems, we use the idea of Fuzzy UML (F-UML) diagrams. In addition, these diagrams have been enriched with performance annotations using proposed Fuzzy-SPT sub profile, the extended version of SPT profile proposed by OMG. Then, these diagrams are mapped into an executable model based on Fuzzy Colored Petri Nets (FCPN) and finally the performance metrics are calculated using the proposed algorithms. We have implemented CPN-Tools for creating and evaluating the FCPN model

Uncertainty-wise Test Case Generation and Minimization for Cyber-Physical Systems

Cyber-Physical Systems (CPSs) typically operate in highly indeterminateenvironmental conditions, which require the development of testing methods that must explicitly consider uncertainty in test design, test generation, and test optimization. Towards this direction, we propose a set of uncertainty-wise test case generation and test case minimizationstrategies that rely on test ready models explicitly specifying subjective uncertainty. We propose two test case generation strategies and four test case minimizationstrategies based on the Uncertainty Theory and multi-objectivesearch. These strategies include a novel methodology for designing and introducing indeterminacy sources in the environment during test execution and a novel set of uncertainty-wise test verdicts. We performed an extensive empirical study to select the bestalgorithm out of eight commonly used multi-objective search algorithms, for each of the four minimizationstrategies, with five use cases of two industrial CPS case studies. The minimizedset of test cases obtained with the best algorithm for each minimizationstrategy were executedon the two real CPSs. The results showed that our best test strategy managed to observe 51% more uncertainties due to unknown indeterminate behaviorsof the physical environmentsof the CPSs as compared to the other test strategies. Also, the same test strategy managed to observe 118% more unknown uncertainties as compared to the unique number of known uncertainties.submittedVersio