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COMMUNITY SOURCE AS A NEW APPROACH TO ENTERPRISE APPLICATION DEVELOPMENT: EXPLORATION OF TECHNOLOGICAL AND MANAGERIAL ISSUESLiu, Manlu. January 2010 (has links)
Community-based open source (community source) has emerged as a new approach of developing enterprise software systems that requires participation and investments from partner institutions. This new approach provides the opportunity for institutions to pool resources together to achieve objectives that are hard to reach individually. In my dissertation, community-based development of enterprise applications is examined in a real world project called Kuali through the following three perspectives: technology perspective, economic perspective and management perspective. Under the technology perspective, the main research question is "how do service-oriented architectures enable technology flexibility in community source?" The Kuali case provides the initial context for understanding the basic concepts and insights surrounding the technological issues in community source. Under the economic perspective, the main research question is "why are institutions interested in investing in community source?" The case study and analytical modeling are used to better understand the decision-making process in community source. Under the management perspective, two main research questions are studied. The first research question is "what are the factors affecting the project success in community source development?" The case study, the surveys and the interviews are conducted to test the community source project success model. The second research question is "what are the motivations for outsourcing software development in community source?" Based on the results of our interview analysis, we propose a research framework for community source outsourcing. In the long term, I would like to develop a generic framework for describing the process of acquiring application software via either commercial, open source, or home grown approach. My research will concentrate on comparing these three application development approaches with a special focus on community source. The main contribution of my dissertation is to provide guideline for strategic planning and decision making in an institution. The finding in this dissertation research will provide significant insights on the selection of various software development approaches that are useful for both researchers and practitioners.
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Evaluating Google App Engine for Enterprise Application DevelopmentKhan, Kashif, Jan, Asar January 2011 (has links)
Context: Google App Engine (GAE) is a cloud computing platform, which allows developers to develop and deploy web based applications on it. It is composed of hundreds of thousands of commodity servers, distributed globally. GAE scales computing resources automatically, and developers only pay for the amount of time their application uses GAE resources. It imposes some restrictions and limitations on the design and development of applications such as execution time limit, lack of global transactions, way of communication with other applications etc. Objectives: In this study, we evaluate Google App Engine from enterprise application development point of view. We analyzed the behavior and architecture of Google App Engine to evaluate its feasibility for enterprise application development and compared it with Amazon Elastic Compute 2 (Amazon cloud service). We also studied Google App Engine storage system, Bigtable, which is a distributed non-SQL based data store. Methods: In this research study, we performed a literature study of the related cloud computing technologies and then a prototype enterprise application was developed for experiment. Results: Our literature study showed that Google App Engine has some limitations and restrictions on the development tools and environment. It does not provide support for global transaction, lacks strict consistency mechanisms, and provides highly virtualized and abstract view of the platform to the developer. Despite these limitations, the literature study and our experiment showed that Google App Engine is suited for applications with high read, searching and large write-stream operations. Google App Engine showed consistent performance as compared to Amazon Elastic Compute 2 in our experiment. Conclusions: We conclude that Google App Engine is a scalable platform while maintaining consistent performance but has some limitations due to its architecture and restrictions imposed on the development tools and environment. These limitations make it non-feasible for some types of enterprise applications, such as applications with high and intensive data computation requirement. But in other cases, such as simple data management and non-transactional applications, Google App Engine is an attractive platform.
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