文章基本信息

标题：Applying Machine learning for Configuring Agile Methods
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作者：Rinky Dwivedi ; Daya Gupta
期刊名称：International Journal of Software Engineering and Its Applications
印刷版ISSN：1738-9984
出版年度：2015
卷号：9
期号：3
页码：29-40
DOI：10.14257/ijseia.2015.9.3.04
出版社：SERSC
摘要：Situational method for satisfying organisation configuration definitions has become an important activity for many modern organisations. In the last few decades many situational method models have been developed but no model has proved to be successful at effectively deliver the customized light-weight methods fulfilling the organisation requirements. The paper introduces an Agile Method engineering approach to find the degree of suitability of agile methods for a particular situation. The introduced process uses associative clustering for finding the cluster of appropriate methods against the organisational requirements-in-hand. The specially designed fuzzy logic controller is used to extract the most appropriate methods from the cluster of appropriate methods. Fuzzy logic controller works in coordination with the databases that have been formed using the previous results and is being trained with the new knowledge. Finally two practical case studies have been discussed to describe how these concepts are applied in practice with industry specified requirements and results are being explored.
关键词：Agile methods; method configuration; situational method for current ; organisational requirement