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  • 标题:Knowledge Management in Global Software Development
  • 本地全文:下载
  • 作者:Sajjan G. Shiva ; Sarah B. Lee ; Lubna A. Shala
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2009
  • 卷号:5
  • 期号:1
  • 页码:6-6
  • DOI:10.1080/15501320802498513
  • 出版社:Hindawi Publishing Corporation
  • 摘要:

    In today's global economy, shrinking business cycles and global competetition are changing the landscape of software development. Frequently, multiple and geographically dispersed development teams are working together on large complex software systems. The complexity of global software development (GSD) warrants investigation into practices for building highly effective geographically diverse teams. GSD introduces challenges such as physical distance, time-zone differences, and diversity of languages and cultures. Frequently, different parts of an organization might use different terms and naming schemes and may have unique ways of expressing concepts. Knowledge of dependencies between software components and a variety of technical platforms must be recognized and shared across the organization. Such a global environment requires a high degree of collaboration and knowledge sharing. The use of a flexible, user-friendly knowledge management system that allows natural language query processing across knowledge captured throughout the software development lifecycle (SDLC) is required to improve knowledge sharing and reuse.

    A variety of knowledge management techniques can be introduced into the SDLC to enhance the understanding and knowledge sharing between dispersed team members. Within the commercial realm, applications to capture and effectively disseminate knowledge are becoming more prevalent; however, many are specific to a business domain rather than focused on facilitating knowledge sharing across the SDLC.

    A high level design of a system that provides an integrated view of work products extracted from different sources in the enterprise, providing “just in times” knowledge to the user either through explicit search capabilities or through intelligence-based alerting that notifies users of new knowledge, is proposed. Our proposed KMS architecture seeks to facilitate a knowledge sharing environment by stressing ease of retrieval through natural language querying and proactive notification. The KMS should be designed to present the most relevant knowledge to the user. With knowledge stored in a variety of formats and on different technical platforms, it is imperative that a tool be provided that will be able to integrate and correlate knowledge from different sources and enable ease of extraction.

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