DocumentCode
2339957
Title
Application of active learning strategy and formalization method in requirement analysis
Author
Zhang, Zhifeng ; Liu, Yuxi
Author_Institution
Software Coll., Zhengzhou Univ. of Light Ind., Zhengzhou, China
fYear
2012
fDate
3-5 June 2012
Firstpage
958
Lastpage
960
Abstract
On base of research and analysis for Bayesian network classifier, active learning strategy and formalization method, this paper proposed a new approach for software requirement analysis based on active learning strategy and formalization method. This approach combined of the Bayesian network, Bayesian network classifier, active learning strategy and formalization method, and improved the approach in the requirement analysis to get the better reusability and the extensibility. This approach eliminated the ambiguity, partialness, inconsistency of system, and provided a reasonable solution for uncertain problem in requirement analysis, therefore improved the performance and the quality of the software.
Keywords
belief networks; formal specification; learning (artificial intelligence); Bayesian network classifier; active learning strategy; formalization method; software requirement analysis; Bayesian methods; Cognition; Educational institutions; Probabilistic logic; Programming; Software; Training; Active learning strategy; B method; Bayesian network classifier; formalization;
fLanguage
English
Publisher
ieee
Conference_Titel
Robotics and Applications (ISRA), 2012 IEEE Symposium on
Conference_Location
Kuala Lumpur
Print_ISBN
978-1-4673-2205-8
Type
conf
DOI
10.1109/ISRA.2012.6219353
Filename
6219353
Link To Document