Article citationsMore>>
Yang, X.-S. (2010) A New Metaheuristic Bat-Inspired Algorithm. In: Gonzlez, J., Pelta, D., Cruz, C., Terrazas, G. and Krasnogor, N., Eds., Nature Inspired Cooperative Strategies for Optimization (NICSO 2010), Vol. 284 of Studies in Computational Intelligence, 65-74. Springer, Berlin and Heidelberg.
has been cited by the following article:
-
TITLE:
Optimizing Software Effort Estimation Models Using Firefly Algorithm
AUTHORS:
Nazeeh Ghatasheh, Hossam Faris, Ibrahim Aljarah, Rizik M. H. Al-Sayyed
KEYWORDS:
Software Quality, Effort Estimation, Metaheuristic Optimization, Firefly Algorithm
JOURNAL NAME:
Journal of Software Engineering and Applications,
Vol.8 No.3,
March
18,
2015
ABSTRACT: Software development effort estimation is
considered a fundamental task for software development life cycle as well as
for managing project cost, time and quality. Therefore, accurate estimation is
a substantial factor in projects success and reducing the risks. In recent
years, software effort estimation has received a considerable amount of
attention from researchersand became a challenge for software industry.
In the last two decades, many researchers and practitioners proposed
statistical and machine learning-based models for software effort estimation.
In this work, Firefly Algorithm is proposed as a metaheuristic optimization
method for optimizing the parameters of three COCOMO-based models. These
models include the basic COCOMO model and other two models proposed in the
literature as extensions of the basic COCOMO model. The developed estimation
models are evaluated using different evaluation metrics. Experimental results
show high accuracy and significant error minimization of Firefly Algorithm over
other metaheuristic optimization algorithms including Genetic Algorithms and
Particle Swarm Optimization.