Earticle

Modern Object oriented programming languages provide the facility of multithreading programming which provides concurrent execution of multiple threads within the same program. Basically, threads provide a way to execute code in parallel within the same program. In high performance computing today, the multi-core CPUs have become more common in nearly all computer systems. These processors have multiple execution cores on a single physical chip. They provide parallelism between instructions and operations. Therefore, the performance measurement of multithreaded programs on these processors is an important aspect. In the present paper, the detailed architectural modeling of a Dual Core processor is done by the use of well known modeling language i.e. the Unified Modeling Language (UML). The UML design for thread execution is also done. On the basis of UML design, performance of multithreaded programs written in JAVA and C# are evaluated and a comparison between these two is also reported through the table and the graphs.

A technical prerequisite for a converged network is a common service delivery platform that is independent from the access networks below. The 3GPP SIP-based IP Multimedia Subsystem is defined for this purpose. By specification, IMS is the first implementation towards reaching converged communications which allows users to communicate with video, audio and multimedia content, via any fixed, mobile and wireless access network type, with controllable QoS. This article analyses the mechanisms of resource allocation and admission control by employing logical interfaces that carry SIP messages.

Regression testing is an expensive, but important process in software testing. Unfortunately, there may be insufficient resources to allow for the re-execution of all test cases during regression testing. In this situation, test case prioritization techniques aim to improve the effectiveness of regression testing by ordering the test cases so that the most beneficial are executed first. In this paper we propose a new test case prioritization technique using Genetic Algorithm (GA). The proposed technique prioritizes subsequences of the original test suite so that the new suite, which is run within a time-constrained execution environment, will have a superior rate of fault detection when compared to rates of randomly prioritized test suites. This experiment analyzes the genetic algorithm with regard to effectiveness and time overhead by utilizing structurally-based criterion to prioritize test cases. An Average Percentage of Faults Detected (APFD) metric is used to determine the effectiveness of the new test case orderings.