Evolutionary Sampling and Software Quality Modeling of High-Assurance Systems
| Autor: | Dennis J. Drown, Taghi M. Khoshgoftaar, Naeem Seliya |
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| Rok vydání: | 2009 |
| Předmět: |
Computer science
Stochastic process business.industry Sampling (statistics) computer.software_genre Machine learning Software quality Evolutionary computation Software metric Computer Science Applications Human-Computer Interaction Control and Systems Engineering Genetic algorithm Oversampling Data mining Software system Artificial intelligence Electrical and Electronic Engineering Cluster analysis business computer Software |
| Zdroj: | IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans. 39:1097-1107 |
| ISSN: | 1558-2426 1083-4427 |
| Popis: | Software quality modeling for high-assurance systems, such as safety-critical systems, is adversely affected by the skewed distribution of fault-prone program modules. This sparsity of defect occurrence within the software system impedes training and performance of software quality estimation models. Data sampling approaches presented in data mining and machine learning literature can be used to address the imbalance problem. We present a novel genetic algorithm-based data sampling method, named evolutionary sampling, as a solution to improving software quality modeling for high-assurance systems. The proposed solution is compared with multiple existing data sampling techniques, including random undersampling, one-sided selection, Wilson's editing, random oversampling, cluster-based oversampling, synthetic minority oversampling technique (SMOTE), and borderline-SMOTE. This paper involves case studies of two real-world software systems and builds C4.5- and RIPPER-based software quality models both before and after applying a given data sampling technique. It is empirically shown that evolutionary sampling improves performance of software quality models for high-assurance systems and is significantly better than most existing data sampling techniques. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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