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This paper considers the importance of knowledge in software development organizations which are highly knowledge-intensive and focuses on knowledge audit in their requirement elicitation process. Requirement elicitation process involves a great deal of knowledge and there are several problems regarding eliciting and using the knowledge in this process. Misunderstanding, undefined scope, conflicting information and constant changes of requirements are some of the problems of requirement elicitation. A knowledge audit model is proposed in this paper to improve the requirement elicitation process by identifying knowledge components and knowledge sources existing in the requirement elicitation process as well as their relationships. A survey is then conducted to prove the validity of the model. The results support that the proposed knowledge components and knowledge audit model improves requirement elicitation.

A vast amount of idle computational power of desktop computers could be utilized throughout desktop grids. For an appropriate utilization, the scheduler, needs to determine clients which are best suited to deliver assigned jobs in time. Diversity of hosts (i.e. OS, hardware and network specifications) and intermittent availability of resources are known issues which complicate the schedulers work. As a solution to this problem, a client-server model consisting two modules for a desktop grid middleware is discussed: a module to forecast machine resource availability in the client side and a module in the server side that recommends clients to the scheduler that are the nearest to job expectations. Historic data, time-series analyses and machine learning are used for this purpose in the modules.

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