EFFECTIVE SOFTWARE TESTING USING GENETIC ALGORITHMS
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Summary
The advantages of the GA approach are that it is simple to use, requires minimal problem specific information, and is able to effectively adapt in dynamically changing environments.
- Type
- article
- Published
- 2011-05-04
- Cited by
- 6
- References
- 17
- OpenAlex
- https://openalex.org/W1500769141
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:54212757
Keywords
Computer science, Software, Software engineering, Search-based software engineering, Simple (philosophy)
References
- The Application of Genetic Algorithms to Resource Scheduling
- Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence
- Using Genetic Algorithms to Schedule Flow Shop Releases
- Scheduling in Real-Time Systems
- Representations for genetic and evolutionary algorithms
- Practical Multiprocessor Scheduling Algorithms for Efficient Parallel Processing
- An Introduction to Genetic Algorithms.
- Genetic algorithms and instruction scheduling
- Genetic Algorithms + Data Structures = Evolution Programs
- Using genetic algorithms to find technical trading rules
- Optimal Scheduling Strategies in a Multiprocessor System
- Genetic algorithms and their applications
- Fundamental Study Theory of genetic algorithms
- Genetic Algorithms
- Genetic Algorithms in Search Optimization and Machine Learning
- Genetic Algorithms in Search, Optimization and Machine Learning
- Genetic algorithms and their applications
- Handbook of Genetic Algorithms
- MULTIPROCESSOR SCHEDULING BASED ON GENETIC ALGORITHMS
- Handbook Of Genetic Algorithms
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- A Methodology For Pattern-Oriented Model-Driven Testing of Reactive Software Systems
- Model driven validation approach for enterprise architecture and motivation extensions
- A Survey on Supporting the Software Engineering Process Using Artificial Intelligence
- Genetic Algorithms: Concepts, Applications in Software Engineering and Test Data Generation using GA and Hamming Distance Approach
- Application of Genetic Algorithm in Software Engineering : A