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Knowledge management initiatives in software testing: A mapping study
DOI:10.1016/j.infsof.2014.05.016.png)
摘要
En 中文
Context: Software testing is a knowledge intensive process, and, thus, Knowledge Management (KM) principles and techniques should be applied to manage software testing knowledge. Objective: This study conducts a survey on existing research on KM initiatives in software testing, in order to identify the state of the art in the area as well as the future research. Aspects such as purposes, types of knowledge, technologies and research type are investigated. Method: The mapping study was performed by searching seven electronic databases. We considered studies published until December 2013. The initial resulting set was comprised of 562 studies. From this set, a total of 13 studies were selected. For these 13, we performed snowballing and direct search to publications of researchers and research groups that accomplished these studies. Results: From the mapping study, we identified 15 studies addressing KM initiatives in software testing that have been reviewed in order to extract relevant information on a set of research questions. Conclusions: Although only a few studies were found that addressed KM initiatives in software testing, the mapping shows an increasing interest in the topic in the recent years. Reuse of test cases is the perspective that has received more attention. From the KM point of view, most of the studies discuss aspects related to providing automated support for managing testing knowledge by means of a KM system. Moreover, as a main conclusion, the results show that KM is pointed out as an important strategy for increasing test effectiveness, as well as for improving the selection and application of suited techniques, methods and test cases. On the other hand, inadequacy of existing KM systems appears as the most cited problem related to applying KM in software testing. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Software testing
Knowledge management
Mapping study
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论文数:
3.8K
被引数:
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引用论文
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