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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; SAS; 198833240; Computer Science and Mathematics; danielle.azar@lau.edul.b; Lebanese American University
URI: http://hdl.handle.net/10725/4822
URL: http://www.ceser.in/ceserp/index.php/ijai/article/view/4613

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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