Efficient Algorithms for Generation of Combinatorial Covering Suites 1st edition by Adrian Dumitrescu ISBN 3540206958 9783540206958

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Product details:

ISBN 10:       3540206958
ISBN 13: 978-3540206958
Author:         Adrian Dumitrescu
 

Efficient Algorithms for Generation of Combinatorial Covering Suites 1st Table of contents:

1. Introduction

   • 1.1 Motivation and Importance of Combinatorial Covering Suites
   • 1.2 Problem Definition: Generation of Covering Suites
   • 1.3 Applications of Covering Suites in Testing and Optimization
   • 1.4 Contributions of the Paper
   • 1.5 Structure of the Paper

2. Background and Related Work

   • 2.1 Overview of Combinatorial Design Theory
   • 2.2 Covering Arrays and Covering Suites
   • 2.3 Properties of Covering Suites: Definition and Key Concepts
   • 2.4 Previous Work on Efficient Generation of Covering Suites
   • 2.5 Comparison of Algorithms for Covering Suite Generation
   • 2.6 Challenges in Generating Covering Suites

3. Preliminaries

   • 3.1 Definition of a Covering Suite
   • 3.2 Types of Covering Designs (e.g., t-covering, partial covering)
   • 3.3 Computational Complexity of Covering Suite Generation
   • 3.4 Notations and Assumptions

4. Algorithmic Approach

   • 4.1 Overview of the Proposed Algorithmic Framework
   • 4.2 Exact Algorithms for Generating Covering Suites
   • 4.3 Heuristic and Approximation Algorithms for Large Instances
   • 4.4 Greedy and Local Search Methods for Efficient Generation
   • 4.5 Parallel and Distributed Algorithms for Large-Scale Problems
   • 4.6 Hybrid Approaches Combining Exact and Approximate Methods

5. Complexity and Performance Analysis

   • 5.1 Time Complexity of Covering Suite Generation Algorithms
   • 5.2 Space Complexity Considerations
   • 5.3 Analysis of Worst-Case and Average-Case Performance
   • 5.4 Comparison with Existing Algorithms in Terms of Efficiency
   • 5.5 Scalability of Algorithms for Large-Scale Instances

6. Experimental Results

   • 6.1 Experimental Setup and Evaluation Metrics
   • 6.2 Benchmarking Algorithms on Synthetic and Real-World Problems
   • 6.3 Performance Results: Time, Space, and Solution Quality
   • 6.4 Case Study: Application in Software Testing (e.g., Test Case Generation)
   • 6.5 Discussion of Experimental Findings and Insights

7. Applications of Covering Suites

   • 7.1 Applications in Software Testing: Test Suite Generation and Fault Detection
   • 7.2 Application in Error Correction and Coding Theory
   • 7.3 Use in Network Design and Communications
   • 7.4 Application in Optimization Problems (e.g., Facility Location, Scheduling)
   • 7.5 Practical Applications in Bioinformatics and Computational Biology

8. Challenges and Limitations

   • 8.1 Scalability of Algorithms for Large Number of Variables and Constraints
   • 8.2 Handling Overlapping and Redundant Solutions in Large Covering Suites
   • 8.3 Extension to Higher-Dimensional Covering Suites
   • 8.4 Dealing with Real-World Constraints in Practical Applications
   • 8.5 Open Problems and Areas for Improvement

9. Future Directions

   • 9.1 Improving Efficiency for Very Large Covering Suites
   • 9.2 Incorporating More Sophisticated Search Techniques (e.g., Simulated Annealing, Genetic Algorithms)
   • 9.3 Further Applications in Dynamic Systems and Real-Time Environments
   • 9.4 Hybridizing Combinatorial Designs with Other Computational Techniques (e.g., Machine Learning, AI)
   • 9.5 Extending Covering Suite Generation to New Problem Domains

10. Conclusion

• 10.1 Summary of Key Contributions
• 10.2 Practical Impact of Efficient Covering Suite Generation Algorithms
• 10.3 Final Remarks and Future Research Directions

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