TELKOMNIKA Telecommunication, Computing, Electronics and Control
Parameter tuning of software effort estimation models using antlion optimization

TELKOMNIKA Telecommunication, Computing, Electronics and Control
Parameter tuning of software effort estimation models using antlion optimization

Antlion optimization algorithm
Parameter tuning
Software effort estimation
The COCOMO model

In this work, the antlion optimization (ALO) is employed due to its
efficiency and wide applicability to estimate the parameters of four modified
models of the basic constructive cost model (COCOMO) model. Three tests
are carried out to show the effectiveness of ALO: first, it is used with Bailey
and Basili dataset for the basic COCOMO Model and Sheta’s Model 1 and 2,
and is compared with the firefly algorithm (FA), genetic algorithms (GA),
and particle swarm optimization (PSO). Second, parameters of Sheta’s
Model 1 and 2, Uysal’s Model 1 and 2 are optimized using Bailey and Basili
dataset; results are compared with directed artificial bee colony algorithm
(DABCA), GA, and simulated annealing (SA). Third, ALO is used with
Basic COCOMO model and four large datasets, results are compared with
hybrid bat inspired gravitational search algorithm (hBATGSA), improved
BAT (IBAT), and BAT algorithms. Results of Test1 and Test2 show that
ALO outperformed others, as for Test3, ALO is better than BAT and IBAT
using MAE and the number of best estimations. ALO proofed achieving
better results than hBATGSA for datasets 2 and 4 out of the four datasets
explored in terms of MAE and the number of best estimates.

Marrwa Abd-AlKareem Alabajee, Najla Akram AlSaati, Taghreed Riyadh Alreffaee

http://journal.uad.ac.id/index.php/TELKOMNIKA

Oct 15, 2020

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