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Developing search strategies for detecting relevant experiments
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DOI：10.1007/s10664-008-9091-7.png)
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摘要
En 中文
Our goal is to analyze the optimality of search strategies for use in systematic reviews of software engineering experiments. Studies retrieval is an important problem in any evidence-based discipline. This question has not been examined for evidence-based software engineering as yet. We have run several searches exercising different terms denoting experiments to evaluate their recall and precision. Based on our evaluation, we propose using a high recall strategy when there are plenty of resources or the results need to be exhaustive. For any other case, we propose optimal, or even acceptable, search strategies. As a secondary goal, we have analysed trends and weaknesses in terminology used in articles reporting software engineering experiments. We have found that it is impossible for a search strategy to retrieve 100% of the experiments of interest (as happens in other experimental disciplines), because of the shortage of reporting standards in the community.
Keyword:
Evidence-based software engineering
Systematic review
Controlled experiment
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.6
论文数:
2.0K
被引数:
5.3K
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Lessons from applying the systematic literature review process within the software engineering domain在软件工程领域应用系统文献综述过程的经验教训
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