Software Cost and Effort Estimation using Ensemble Duck Traveler Optimization Algorithm (eDTO) in Earlier Stage
Main Article Content
Abstract
Software engineering is a hot and needed research area for early and also accurate estimation of cost, effort, time to achieving quality of software project. Accuracy is the primary factor involving victim of software cost estimation and increasing the productivity of any workstation. Algorithmic and non-algorithmic models are helped to predict the cost in earlier stage without optimizing any constraints. Nowadays new optimization algorithms based on both the nature inspired based and swarm intelligence based are help to introduce new cost, effort and time estimation in earlier stage of design efficiently. Here, under estimation and over estimation should be optimized using new meta-heuristic algorithm inspired by Duck Flock. For the proposed algorithm eDTO, ACC (Accuracy), VAR (Variance), metrics are used to evaluating the results using NASA 93 standard dataset. Evaluation results are compared with existing COCOMO, NN, SBA and proved that the eDTO having high accuracy and low miscalculation rate.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
