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On the use of relevance feedback in IR-based concept location

机译:在基于IR的概念定位中使用相关性反馈

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Concept location is a critical activity during software evolution as it produces the location where a change is to start in response to a modification request, such as, a bug report or a new feature request. Lexical-based concept location techniques rely on matching the text embedded in the source code to queries formulated by the developers. The efficiency of such techniques is strongly dependent on the ability of the developer to write good queries. We propose an approach to augment information retrieval (IR) based concept location via an explicit relevance feedback (RF) mechanism. RF is a two-part process in which the developer judges existing results returned by a search and the IR system uses this information to perform a new search, returning more relevant information to the user. A set of case studies performed on open source software systems reveals the impact of RF on IR based concept location.
机译:概念定位是软件开发过程中的一项关键活动,因为它会根据修改请求(例如错误报告或新功能请求)生成开始更改的位置。基于词法的概念定位技术依赖于将源代码中嵌入的文本与开发人员制定的查询进行匹配。这种技术的效率在很大程度上取决于开发人员编写良好查询的能力。我们提出一种通过显式相关性反馈(RF)机制增强基于信息检索(IR)的概念定位的方法。 RF是一个分为两部分的过程,其中开发人员判断搜索返回的现有结果,IR系统使用此信息执行新搜索,将更多相关信息返回给用户。在开源软件系统上进行的一系列案例研究揭示了RF对基于IR的概念定位的影响。

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