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首页> 外文会议>2nd International workshop on recommendation systems for software engineering 2010 >Towards Knowledge Assisted Agile Requirements Evolution
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Towards Knowledge Assisted Agile Requirements Evolution

机译：迈向知识辅助的敏捷需求演进

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This paper presents work on a recommendation system for Knowledge assisted Agile Requirements Evolution (K-gileRE). We treat requirements engineering as a special case of knowledge engineering and emphasize the fact that providing a domain knowledge edge can impart agility to the requirements definition exercise. The approach differs from existing agile methods in that it seamlessly incorporates a domain knowledge base into an agile requirements definition framework and explicitly provides to requirement analysts, relevant online domain specific recommendations based on underlying ontologies. The framework presents a 'domain knowledge seed' to requirement analysts. The seed provides a view of core features in a given domain and associated knowledge elements such as business processes, rules, policies, partial data models, use cases and test cases,. These in turn are mapped with agile requirements elements such as user stories, features, tasks, product backlog, sprints and prototype plans. The requirement analyst can evolve the seed to suit her specific project needs. As she modifies and evolves the seed specification, she receives domain-specific online recommendations to improve the correctness, consistency and completeness of her requirement specification documents and executable models. Using the domain knowledge seed as a point of departure provides a jump-start to her project. Each exercise of requirements definition thus becomes an evolution from the seed instead of the traditional 'clean slate' Requirements Engineering (RE) that typically starts from the scratch. Hence, the term K-gileRE. We elaborate how K-gileRE helps in practicing the essence of agile doctrines while defining software requirements by providing just-in-time recommendations.
机译：本文介绍了有关知识辅助敏捷需求演化（K-gileRE）推荐系统的工作。我们将需求工程视为知识工程的特例，并强调提供领域知识优势可以为需求定义工作赋予敏捷性的事实。该方法与现有敏捷方法的不同之处在于，它无缝地将领域知识库整合到敏捷需求定义框架中，并根据基本本体向需求分析人员明确提供了相关的在线领域特定建议。该框架为需求分析人员提供了“领域知识种子”。种子提供了给定领域中的核心功能以及相关知识元素的视图，例如业务流程，规则，策略，部分数据模型，用例和测试用例。这些又与敏捷需求元素映射在一起，例如用户故事，功能，任务，产品积压，冲刺和原型计划。需求分析师可以根据自己的特定项目需求来发展种子。在修改和发展种子规范时，她会收到特定领域的在线建议，以提高其需求规范文档和可执行模型的正确性，一致性和完整性。使用领域知识种子作为出发点，可以为她的项目提供一个快速的起点。因此，每次需求定义的实践都是从种子开始的，而不是通常从头开始的传统“干净的”需求工程（RE）。因此，术语K-gileRE。我们将详细说明K-gileRE如何通过提供及时的建议来帮助实践敏捷学说的本质，同时定义软件需求。

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