Using COCOMO Dataset Effort Estimation for Developing Software
Manohar K. Kodmelwar1, S.D. Joshi2, V. Khanna3
1Manohar K. Kodmelwar, Research Scholar, Bharath University, Chennai (Tamil Nadu), India.
2S.D. Joshi, Faculty of Engineering and Technology, Bhartividyapth, Pune (Maharashtra), India.
3V. Khanna, Department of Information Technology, Bharath University, Chennai (Tamil Nadu), India.
Manuscript received on 07 February 2019 | Revised Manuscript received on 29 March 2019 | Manuscript Published on 28 April 2019 | PP: 111-113 | Volume-7 Issue-5C February 2019 | Retrieval Number: E10270275C19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The development of software according to the required demand of customer. So it is important to find the effort required to develop the software. The estimation is done using the particle swarm optimization technique by applying the weights in the neural network. The usage of NN helps in estimating the efforts of the software with less cost and failure rates. The NN is utilized together with optimization to attain an enhanced outcome. The dataset utilized as input to the proposed system is the COCOMO dataset. The actual effort in the COCOMO dataset is measured by person-month which represents the number of months that one person needs to develop a given project. The proposed method gives the accurate estimation compared to the existing models.
Keywords: COCOMO, NN, Hybrid Swarm Particle Optimization, Credit Assignment Path.
Scope of the Article: Systems and Software Engineering