Welcome to the InfoSci Platform
Reference Hub4
The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models

The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models

Maryam Hassani Saadi, Vahid Khatibi Bardsiri, Fahimeh Ziaaddini
Copyright: © 2015 |Volume: 6 |Issue: 4 |Pages: 30
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466677524|DOI: 10.4018/IJAEC.2015100104
Cite Article Cite Article

MLA

Saadi, Maryam Hassani, et al. "The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models." IJAEC vol.6, no.4 2015: pp.39-68. http://doi.org/10.4018/IJAEC.2015100104

APA

Saadi, M. H., Bardsiri, V. K., & Ziaaddini, F. (2015). The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models. International Journal of Applied Evolutionary Computation (IJAEC), 6(4), 39-68. http://doi.org/10.4018/IJAEC.2015100104

Chicago

Saadi, Maryam Hassani, Vahid Khatibi Bardsiri, and Fahimeh Ziaaddini. "The Application of Meta-Heuristic Algorithms to Improve the Performance of Software Development Effort Estimation Models," International Journal of Applied Evolutionary Computation (IJAEC) 6, no.4: 39-68. http://doi.org/10.4018/IJAEC.2015100104

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

One of the major activities in effective and efficient production of software projects is the precise estimation of software development effort. Estimation of the effort in primary steps of software development is one of the most important challenges in managing software projects. Some reasons for these challenges such as: discordant software projects, the complexity of the manufacturing process, special role of human and high level of obscure and unusual features of software projects can be noted. Predicting the necessary efforts to develop software using meta-heuristic optimization algorithms has made significant progressions in this field. These algorithms have the potent to be used in estimation of the effort of the software. The necessity to increase estimation precision urged the authors to survey the efficiency of some meta-heuristic optimization algorithms and their effects on the software projects. To do so, in this paper, they investigated the effect of combining various optimization algorithms such as genetic algorithm, particle swarm optimization algorithm and ant colony algorithm on different models such as COCOMO, estimation based on analogy, machine learning methods and standard estimation models. These models have employed various data sets to evaluate the results such as COCOMO, Desharnais, NASA, Kemerer, CF, DPS, ISBSG and Koten & Gary. The results of this survey can be used by researchers as a primary reference.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.