DocumentCode :
324641
Title :
Software quality measurement: concepts and fuzzy neural relational model
Author :
Pedrycz, W. ; Peters, J.F. ; Ramanna, S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Manitoba Univ., Winnipeg, Man., Canada
Volume :
2
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
1026
Abstract :
A fuzzy neural relational model of software quality derived from the McCall hierarchical software quality measurement framework (HSQF), is introduced. The HSQF has three fundamental levels (factors→criteria→metrics) which has a rather natural generalization in the context of fuzzy sets. Vectors of factors, criteria, and metrics are treated as fuzzy sets. On each level, fuzzy objects (fuzzy set and fuzzy relation) are introduced. A learning algorithm is proposed to calibrate the relations at the topmost levels of the software quality model. A learning scenario and detailed learning formulas are given. A brief illustration of the model is also given
Keywords :
fuzzy set theory; learning (artificial intelligence); neural nets; software metrics; software quality; McCall hierarchical software quality measurement framework; fuzzy neural relational model; fuzzy objects; fuzzy sets; learning algorithm; Computational intelligence; Electric variables measurement; Fuzzy sets; Laboratories; Q factor; Quality management; Software measurement; Software metrics; Software quality; Software testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7584
Print_ISBN :
0-7803-4863-X
Type :
conf
DOI :
10.1109/FUZZY.1998.686259
Filename :
686259
Link To Document :
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