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TextRank based search term identification for software change tasks

机译：基于Textrank的搜索词标识软件更改任务

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摘要

During maintenance, software developers deal with a number of software change requests. Each of those requests is generally written using natural language texts, and it involves one or more domain related concepts. A developer needs to map those concepts to exact source code locations within the project in order to implement the requested change. This mapping generally starts with a search within the project that requires one or more suitable search terms. Studies suggest that the developers often perform poorly in coming up with good search terms for a change task. In this paper, we propose and evaluate a novel TextRank-based technique that automatically identifies and suggests search terms for a software change task by analyzing its task description. Experiments with 349 change tasks from two subject systems and comparison with one of the latest and closely related state-of-the-art approaches show that our technique is highly promising in terms of suggestion accuracy, mean average precision and recall.
机译：在维护期间，软件开发人员处理许多软件更改请求。这些请求通常使用自然语言文本编写，并且它涉及一个或多个域相关概念。开发人员需要将这些概念映射到项目中的精确源代码位置，以便实现所请求的更改。该映射通常以项目内的搜索开始，该搜索需要一个或多个合适的搜索项。研究表明，开发人员在提出更好的搜索条件时经常表现不佳。在本文中，我们提出并评估了一种基于新的基于Textrank的技术，它通过分析其任务描述来自动识别并建议搜索软件更改任务的搜索条件。实验与两个主题系统的349个改变任务以及与最新和密切相关的最先进的方法之一的比较表明，在建议准确性方面，我们的技术具有高度前景，平均精度和召回。

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