An Ant Colony Optimization Heuristic to Optimize Prediction of Stability of Object-Oriented Components

Azar, Danielle; Harmani, Haidar; Zgheib, Grace

An Ant Colony Optimization Heuristic to Optimize Prediction of Stability of Object-Oriented Components

Azar, Danielle; Harmani, Haidar; Zgheib, Grace

URI: http://hdl.handle.net/10725/5372

URL: http://ieeexplore.ieee.org/abstract/document/7300981/

DOI: http://dx.doi.org/10.1109/IRI.2015.45

Date: 2017-03-15

Terms of Use: This item is made available under the terms and conditions applicable to " Conference Paper / Proceeding ", as set forth at: http://libraries.lau.edu.lb/research/laur/terms-of-use/articles.php

Abstract:

The IEEE 729-1983 Standard defines software quality as "the composite characteristics of software that determine the degree to which the software in use will meet the expectations of the customer." Assessing software quality in the early stages of design and development is crucial in reducing time and effort. Various metrics have been proposed for estimating software quality characteristics from measurable attributes. This paper presents an Ant Colony Optimization (ACO) approach that improves the prediction accuracy of software quality estimation models by intensifying the search around the metric neighborhood. The method has been implemented, and favorable results comparisons are reported.

Citation:

Harmanani, H., Azar, D., Zgheib, G., & Kozhaya, D. (2015, August). An ant colony optimization heuristic to optimize prediction of stability of object-oriented components. In Information Reuse and Integration (IRI), 2015 IEEE International Conference on (pp. 225-228). IEEE.