Software quality measurement: Concepts and fuzzy neural relational model

被引：0

作者：

Pedrycz, W ^{[1
]}

Peters, JF ^{[1
]}

Ramanna, S ^{[1
]}

机构：

[1] Univ Manitoba, Dept Elect & Comp Engn, Computat Intelligence Lab, Winnipeg, MB R3T 2N2, Canada

来源：

1998 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS AT THE IEEE WORLD CONGRESS ON COMPUTATIONAL INTELLIGENCE - PROCEEDINGS, VOL 1-2 | 1998年

关键词：

software quality; software metrics; fuzzy sets; learning; neural networks;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：1026 / 1031

页数：6

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