Title :
Definition of software metrics for software project development by using fuzzy sets and logic
Author :
Mirseidova, S. ; Atymtayeva, L.
Author_Institution :
Kazakh-British Tech. Univ., Almaty, Kazakhstan
Abstract :
Software metrics measure certain properties of the software or its specifications. As quantitative measurements are required in all the sciences, there are ongoing efforts among computer science practitioners and academics to apply analogous approaches to software development process. The main aim is to provide objective, reproducible and quantitative measure that can have many useful applications in such important parts of software project management as the schedule and budget planning, cost estimation, quality assurance, software debugging, performance optimization and optimal staff task assignments as well as in the whole software development life cycle. There exist a number of techniques for modeling software metrics including FPA estimation (mean-based, median-based), LS regression, LMS regression, Neural Networks, and Fuzzy Logic. In this paper we are going to talk about singularities of applying Fuzzy Logic approach to the software metrics modeling.
Keywords :
fuzzy logic; fuzzy set theory; software development management; software metrics; FPA estimation; LMS regression; LS regression; budget planning; cost estimation; fuzzy logic; fuzzy set; least mean squares regression; least squares regression; mean-based estimation; median-based estimation; neural network; performance optimization; quality assurance; quantitative measurement; schedule management; software debugging; software development life cycle; software metrics; software project development; software property; software specification; staff task assignment; fuzzy logic and sets; software metrics; software project management;
Conference_Titel :
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location :
Kobe
Print_ISBN :
978-1-4673-2742-8
DOI :
10.1109/SCIS-ISIS.2012.6505336