Supporting evidence-based Software Engineering with collaborative information retrieval

H. Ramampiaro, D. Cruzes, R. Conradi, Manoel G. Mendonça
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引用次数: 11

Abstract

The number of scientific publications is constantly increasing, and the results published on Empirical Software Engineering are growing even faster. Some software engineering publishers have began to collaborate with research groups to make available repositories of software engineering empirical data. However, these initiatives are limited due to issues related to the available search tools. As a result, many researchers in the area have adopted a semi-automated approach for performing searches for systematic reviews as a mean to extract empirical evidence from published material. This makes this activity labor intensive and error prone. In this paper, we argue that the use of techniques from information retrieval, as well as text mining, can support systematic reviews and improve the creation of repositories of SE empirical evidence.
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支持基于证据的软件工程与协同信息检索
科学出版物的数量在不断增加,而发表在Empirical Software Engineering上的结果增长得更快。一些软件工程出版商已经开始与研究小组合作,以提供软件工程经验数据的可用存储库。然而,由于与可用的搜索工具相关的问题,这些举措受到了限制。因此,该领域的许多研究人员采用了半自动化的方法来执行系统评论的搜索,作为从已发表材料中提取经验证据的一种手段。这使得该活动是劳动密集型的,并且容易出错。在本文中,我们认为信息检索技术的使用,以及文本挖掘,可以支持系统评论和改进SE经验证据库的创建。
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