Tuning of COCOMO II Model Parameters for Estimating Software Development Effort using GA for PROMISE Project Data Set | Zendy

Chandra Shekhar Yadav | Zendy; Raghuraj Singh | Zendy

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Tuning of COCOMO II Model Parameters for Estimating Software Development Effort using GA for PROMISE Project Data Set

Author(s) -

Chandra Shekhar Yadav,

Raghuraj Singh

Publication year - 2014

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/15542-4367

Subject(s) - cocomo , computer science , set (abstract data type) , software , data set , data mining , software development , software engineering , operations research , artificial intelligence , programming language , software construction , mathematics

In this paper, we have tuned the parameters of COCOMO II model to estimate the software development effort using genetic algorithm (GA). Results obtained by applying GA are have been compared with results obtained by applying particle swarm optimization (PSO) published in previous paper. COCOMO II model is modified by introducing some more parameters to predict the software development effort more precisely. The performance of this parametric model is tested on the past PROMISE and NASA projects data set. General Terms Genetic Algorithm, Particle Swarm Optimization

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