PCA Analysis of Few Parameters Role in Software Development
Author(s) -
K. Seetharam,
Venkata Subba Reddy,
Laxmi B Rananavare
Publication year - 2011
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/1889-2506
Subject(s) - computer science , software , software engineering , programming language
Principal component analysis is one of the dimension reduction methods with the goal of using the correlation structure among the predictor variables. Qualitative/quantitative measurement of software quality related aspects in all stages of software development are desirable [9,10,11,12].Any measurement using any element in the software metrics is helpful for analysis in the set of software quality metrics. In this paper seventeen software metric variables [4], are considered. Four cases are carried out using principle component analysis. First analysis is with size as predominant factor. Second analysis is with effort as predominant factor. Third analysis is with duration as predominant factor. Finally all the three association taken together used for analysis of quality performance. The analysis of variables is to identify the dimension that are latent [7,8].
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom