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A combined ant colony optimization and simulated annealing algorithm to assess Stability and fault-proneness of classes based on internal software quality attributes

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A combined ant colony optimization and simulated annealing algorithm to assess Stability and fault-proneness of classes based on internal software quality attributes

Azar, Danielle; Fayad, Karl; Daoud, Charbel
URI: http://hdl.handle.net/10725/4822
URL: http://www.ceser.in/ceserp/index.php/ijai/article/view/4613
Date: 2016-11-16
Terms of Use: This item is made available under the terms and conditions applicable to " Article ", as set forth at: http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php

Abstract:

Azar, D., Fayad, K., & Daoud, C. (2016). A Combined Ant Colony Optimization and Simulated Annealing Algorithm to Assess Stability and Fault-Proneness of Classes Based on Internal Software Quality Attributes. International Journal of Artificial Intelligence™, 14(2), 137-156.

Citation:

Azar, D., Fayad, K., & Daoud, C. (2016). A Combined Ant Colony Optimization and Simulated Annealing Algorithm to Assess Stability and Fault-Proneness of Classes Based on Internal Software Quality Attributes. International Journal of Artificial Intelligence™, 14(2), 137-156.

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