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Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities [Kõva köide]

Software development and design is an intricate and complex process that requires a multitude of steps to ultimately create a quality product. One crucial aspect of this process is minimizing potential errors through software fault prediction.

Enhancing Software Fault Prediction With Machine Learning: Emerging Research and Opportunities is an innovative source of material on the latest advances and strategies for software quality prediction. Including a range of pivotal topics such as case-based reasoning, rate of improvement, and expert systems, this book is an ideal reference source for engineers, researchers, academics, students, professionals, and practitioners interested in novel developments in software design and analysis.
Preface vi
Chapter 1 Software Quality
1(8)
Chapter 2 Literature Survey and Scope of the Present Work
9(10)
Chapter 3 Overview of Machine Learning Approaches
19(15)
Chapter 4 Methods of Software Quality Prediction With Similarity Measures: As an Expert System
34(23)
Chapter 5 Software Quality Measures as Degree of Excellence
57(10)
Chapter 6 Understanding the State of Quality of Software
67(12)
Chapter 7 Estimation and Evaluation of Software Quality at a Particular Stage of Software Development
79(24)
Conclusion 103(3)
Glossary 106(2)
Related Readings 108(20)
Index 128
Ekbal Rashid, Aurora's Technological and Research Institute, India.