Methodology for Validating Software Metrics
IEEE Transactions on Software Engineering
Prediction of Software Reliability Using Connectionist Models
IEEE Transactions on Software Engineering
Rule-based fuzzy classification for software quality control
Fuzzy Sets and Systems - Special issue on industrial applications
Measuring the software process: a practical guide to functional measurements
Measuring the software process: a practical guide to functional measurements
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
Fuzzy clustering in software reusability
Software—Practice & Experience
Self-organizing maps
Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
Managing risk: methods for software systems development
Managing risk: methods for software systems development
Software development cost estimation integrating neural network with cluster analysis
Information and Management
Empirical Data Modeling in Software Engineering Using Radial Basis Functions
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
A Framework of Software Measurement
A Framework of Software Measurement
Computational Intelligence: An Introduction
Computational Intelligence: An Introduction
Software Metrics: A Rigorous Approach
Software Metrics: A Rigorous Approach
Computational Intelligence in Software Engineering
Computational Intelligence in Software Engineering
On Building Prediction Systems for Software Engineers
Empirical Software Engineering
Heuristic Risk Assessment Using Cost Factors
IEEE Software
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
Granular computing: an emerging paradigm
Granular computing: an emerging paradigm
Assessing Neural Networks as Guides for Testing Activities
METRICS '96 Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results
Fuzzy logic = computing with words
IEEE Transactions on Fuzzy Systems
Software Development Effort Estimation Using Fuzzy Logic: A Case Study
ENC '05 Proceedings of the Sixth Mexican International Conference on Computer Science
Hybrid Intelligence in Software Release Planning
International Journal of Hybrid Intelligent Systems
Predictive accuracy comparison of fuzzy models for software development effort of small programs
Journal of Systems and Software
Knowledge management for computational intelligence systems
HASE'04 Proceedings of the Eighth IEEE international conference on High assurance systems engineering
Software effort estimation based on optimized model tree
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
MCPR'11 Proceedings of the Third Mexican conference on Pattern recognition
Systematically evolving configuration parameters for computational intelligence methods
PReMI'05 Proceedings of the First international conference on Pattern Recognition and Machine Intelligence
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
Search-based software engineering: Trends, techniques and applications
ACM Computing Surveys (CSUR)
Vertical software industry evolution: The impact of software costs and limited customer base
Information and Software Technology
Diversity oriented test data generation using metaheuristic search techniques
Information Sciences: an International Journal
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Software Engineering is inherently knowledge intensive. Software processes and products are human centered. The technology of Computational Intelligence (CI) intensively exploits various mechanisms of interaction with humans and processes domain knowledge with intent of building intelligent systems. As commonly perceived, CI dwells on three highly synergistic technologies of neural networks, fuzzy sets (or granular computing, in general) and evolutionary optimization. As the software complexity grows and the diversity of software systems skyrocket, it becomes apparent that there is a genuine need for a solid, efficient, designer-oriented vehicle to support software analysis, design, and implementation at various levels. The research agenda makes CI a highly compatible and appealing vehicle to address the needs of knowledge rich environment of Software Engineering. The objective of this study is to identify and discuss synergistic links emerging between Software Engineering and Computational Intelligence. We show how CI --- based models contribute to the methodology of constructing models of software processes and products. Several selected examples (including software cost estimation, quality, and software measures) are included.