Title
Predictive accuracy comparison of fuzzy models for software development effort of small programs
Abstract
Regression analysis to generate predictive equations for software development effort estimation has recently been complemented by analyses using less common methods such as fuzzy logic models. On the other hand, unless engineers have the capabilities provided by personal training, they cannot properly support their teams or consistently and reliably produce quality products. In this paper, an investigation aimed to compare personal Fuzzy Logic Models (FLM) with a Linear Regression Model (LRM) is presented. The evaluation criteria were based mainly upon the magnitude of error relative to the estimate (MER) as well as to the mean of MER (MMER). One hundred five small programs were developed by thirty programmers. From these programs, three FLM were generated to estimate the effort in the development of twenty programs by seven programmers. Both the verification and validation of the models were made. Results show a slightly better predictive accuracy amongst FLM and LRM for estimating the development effort at personal level when small programs are developed.
Year
DOI
Venue
2008
10.1016/j.jss.2007.08.027
Journal of Systems and Software
Keywords
Field
DocType
fuzzy model,software effort estimation,linear regression model,linear regression,development effort,software engineering education,personal fuzzy logic models,common method,small program,software development effort estimation,predictive accuracy comparison,fuzzy logic,predictive accuracy,personal level,personal training,personal software process,predictive equation,verification and validation,regression analysis,software development
Personal software process,Verification and validation,Computer science,Regression analysis,Fuzzy logic,Software development effort estimation,Artificial intelligence,Software development,Machine learning,Linear regression
Journal
Volume
Issue
ISSN
81
6
The Journal of Systems & Software
Citations 
PageRank 
References 
12
0.79
17
Authors
3