Empirical Data Modeling in Software Engineering Using Radial Basis Functions

Authors:
Miyoung Shin;Amrit L. Goel
Affiliations:
Electronics and Telelcommunications Research Institute, Taejon, Korea;Syracuse Univ., Syracuse, NY
Venue:
IEEE Transactions on Software Engineering
Year:
2000

Citing 13
Cited 25

An empirical validation of software cost estimation models

Communications of the ACM
Neural networks and the bias/variance dilemma

Neural Computation
On radial basis function nets and kernel regression: statistical consistency, convergence rates, and receptive field size

Neural Networks
Software engineering data analysis techniques (tutorial)

ICSE '97 Proceedings of the 19th international conference on Software engineering
Algorithmic stability and sanity-check bounds for leave-one-out cross-validation

COLT '97 Proceedings of the tenth annual conference on Computational learning theory
Validating the defect detection performance advantage of group designs for software reviews: report of a laboratory experiment using program code

ESEC '97/FSE-5 Proceedings of the 6th European SOFTWARE ENGINEERING conference held jointly with the 5th ACM SIGSOFT international symposium on Foundations of software engineering
Understanding the sources of variation in software inspections

ACM Transactions on Software Engineering and Methodology (TOSEM)
Estimating Software Project Effort Using Analogies

IEEE Transactions on Software Engineering
Neural Networks for Pattern Recognition

Neural Networks for Pattern Recognition
Software Engineering Economics

Software Engineering Economics
On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality

Data Mining and Knowledge Discovery
A meta-model for software development resource expenditures

ICSE '81 Proceedings of the 5th international conference on Software engineering
Design and evaluation of radial basis function model for function approximation

Design and evaluation of radial basis function model for function approximation

Computational intelligence as an emerging paradigm of software engineering

SEKE '02 Proceedings of the 14th international conference on Software engineering and knowledge engineering
Predicting project delivery rates using the Naive-Bayes classifier

Journal of Software Maintenance: Research and Practice
Optimization and response surfaces: Gaussian radial basis functions for simulation metamodeling

Proceedings of the 34th conference on Winter simulation: exploring new frontiers
Letters: Estimation of software project effort with support vector regression

Neurocomputing
A GA-based feature selection and parameters optimization for support vector regression applied to software effort estimation

Proceedings of the 2008 ACM symposium on Applied computing
An approach to fuzzy granule-based hierarchical polynomial networks for empirical data modeling in software engineering

Information and Software Technology
Structural and parametric design of fuzzy inference systems using hierarchical fair competition-based parallel genetic algorithms and information granulation

International Journal of Approximate Reasoning
A study of project selection and feature weighting for analogy based software cost estimation

Journal of Systems and Software
Improved estimation of software project effort using multiple additive regression trees

Expert Systems with Applications: An International Journal
Understanding cost drivers of software evolution: a quantitative and qualitative investigation of change effort in two evolving software systems

Empirical Software Engineering
Genetically optimized rule-based fuzzy polynomial neural networks: synthesis of computational intelligence technologies

RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
GA-based method for feature selection and parameters optimization for machine learning regression applied to software effort estimation

Information and Software Technology
Evaluating software cost estimation models using particle swarm optimisation and fuzzy logic for NASA projects: a comparative study

International Journal of Bio-Inspired Computation
A shift-invariant morphological system for software development cost estimation

Expert Systems with Applications: An International Journal
Modeling of the charging characteristic of linear-type superconducting power supply using granular-based radial basis function neural networks

Expert Systems with Applications: An International Journal
Systematic literature review of machine learning based software development effort estimation models

Information and Software Technology
A performance study of gaussian kernel classifiers for data mining applications

ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Modeling software component criticality using a machine learning approach

AIS'04 Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems
Hybrid morphological methodology for software development cost estimation

Expert Systems with Applications: An International Journal
Genetically optimized hybrid fuzzy neural networks in modeling software data

MDAI'05 Proceedings of the Second international conference on Modeling Decisions for Artificial Intelligence
Computational intelligence in software cost estimation: an emerging paradigm

ACM SIGSOFT Software Engineering Notes
Relation-based neurofuzzy networks with evolutionary data granulation

Mathematical and Computer Modelling: An International Journal
Towards an early software estimation using log-linear regression and a multilayer perceptron model

Journal of Systems and Software
Functional Link Artificial Neural Networks for Software Cost Estimation

International Journal of Applied Evolutionary Computation
Software development cost estimation using similarity difference between software attributes

Proceedings of the 2013 International Conference on Information Systems and Design of Communication

Quantified Score

Hi-index	0.01

Visualization

Abstract

Many empirical studies in software engineering involve relationships between various process and product characteristics derived via linear regression analysis. In this paper, we propose an alternative modeling approach using Radial Basis Functions (RBFs) which provide a flexible way to generalize linear regression function. Further, RBF models possess strong mathematical properties of universal and best approximation. We present an objective modeling methodology for determining model parameters using our recent SG algorithm, followed by a model selection procedure based on generalization ability. Finally, we describe a detailed RBF modeling study for software effort estimation using a well-known NASA dataset.