This book focusses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection, and so forth.

1. Implementation of Artificial Intelligence Techniques for Improving Software Engineering. 2. Software effort estimation: Machine learning vs. Hybrid algorithms. 3. Implementation of Data Mining Techniques for Software Development Effort Estimation. 4. Empirical Software Measurements with Machine Learning. 5. Project Estimation And Scheduling Using Computational Intelligence. 6. Application of Intuitionistic Fuzzy Similarity Measures in Strategic Decision-Making. 7. Nature-Inspired Approaches to Test Suite Minimization for Regression Testing. 8. Identification and Construction of Reusable Components from Object-Oriented Legacy Systems using various Software Artifacts. 9. A Software Component Evaluation and Selection Approach Using Fuzzy Logic. 10. Smart Predictive Analysis for Testing Messaging-passing Applications. 11. Status of Agile Practices in the Software Industry in 2019. 12. Agile Methodologies: A Performance Analysis To Enhance Software Quality. 13. Pre-Trained Deep Neural Networks for Age Prediction from IRIS Biometrics. 14. Hybrid Intelligent Decision Support Systems to Select The Optimum Fuel Blend in CI Engine. 15. Understanding the Significant Challenges of Software Engineering in Cloud Environment.