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ADSD (Agile Distributed Software Development) is a growing trend for software development organizations to develop quality software with limited cost and time. However, it gives rise to additional situational challenges. Situational variations result in unstable agile architecture which gets highly affected. Although the present literature focuses on agile architecture but effect of situational variation on the agile architecture still needs consideration. One possible solution is development of conceptual model and incorporation of multiple situational factors. This research study aims to identify the most relevant situations and propose situational ADSD approach for the development of situation-based software architecture framework for agile distributed projects. The study focuses on agile methods, rendering identified situational variations. The approach is developed through analyzing data from literature and their associated work documents. Comprehensive survey helps to bridge the gaps from conceptual to architecture model. The experimental results are acquired through both practical and statistical analysis. The results support Conway’s law, e.g. correlation that maps architecture with the communication and coordination needs. Correlation results show that architecture has major contribution in ADSD and validate the relationship among conceptual model and architecture model. The results also suggest that stable architecture in ADSD can positively affect the product.

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Highly-configurable systems are such systems which are not developed for single scenario. However, perhaps they have variable functionality and they are developed for hybrid scenarios. Producing a good highly-configurable system within time and with customer satisfaction is not easy. Handling requirements effectively in such a way that it take least time to market, is one of the most difficult tasks in highly-configurable system. In this paper, a quantitative requirement prioritization technique for highlyconfigurable systems is proposed. This technique involves all stakeholders and can be used primarily for large scale software projects. The proposed technique is evaluated by taking a case study of the highlyconfigurable point of sale for automotive industry. The result shows that the proposed technique provides promising results and can be enhanced with more future work. INDEX TERMS Customer value creation, highly-configurable system, quantitative approach, requirement prioritization.

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Software development globally an important business nowadays and also there are different issues related to software development process especially in change management process when there is change in requirement due to lack of communication, coordination and expert knowledge not properly manage. The aim of this paper is to provide and proposed framework to manage RCM (Requirement Change Management) using CBR (Cased Based Reasoning) technique effectively and intelligently. CBR to solve change in requirement on the base of previous knowledge and experience evaluated the proposed framework through experimental study. The experimental study depicted that proposed framework improved requirement change management in GSD (Globally Software Development) instead of other methods for change management of requirements in globally dispersed environment effectively.

To survive in the competitive environment, most organizations have adopted componentbased software development strategies in the rapid technology advancement era and the proper utilization of cloud-based services. To facilitate the continuous configuration, reduce complexity, and faster system delivery for higher user satisfaction in dynamic scenarios. In cloud services, customers select services from web applications dynamically. Healthcare body sensors are commonly used for diagnosis and monitoring patients continuously for their emergency treatment. The healthcare devices are connected with mobile or laptop etc. on cloud environment with network and frequently change applications. Thus, organizations rely on regression testing during changes and implementation to validate the quality and reliability of the system after the alteration. However, for a large application with limited resources and frequently change component management activities in the cloud computing environment, component-based system verification is difficult and challenging due to irrelevant and redundant test cases and faults. In this study, proposed a test case selection and prioritization framework using a design pattern to increase the faults detection rate. First, we select test cases on frequently accessed components using observer patterns and, secondly, prioritize test cases on adopting some strategies. The proposed framework was validated by an experiment and compared with other techniques (previous faults based and random priority). Hence, experimental results show that the proposed framework successfully verified changes. Subsequently, the proposed framework increases the fault detection rate (i.e., more than 90%) than previous faults based and random priority (i.e., more than 80% respectively).

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