Optimizing Basic COCOMO Model Using Simplified Genetic Algorithm

The estimation of software effort is an essential and crucial activity for the software development life cycle. In recent years, many researchers and software industries have given significant attention on the estimation of software effort. In industry, effort is used for planning, budgeting and dev...

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Bibliographic Details
Published in:Procedia computer science 2016, Vol.89, p.492-498
Main Authors: Sachan, Rohit Kumar, Nigam, Ayush, Singh, Avinash, Singh, Sharad, Choudhary, Manjeet, Tiwari, Avinash, Kushwaha, Dharmender Singh
Format: Article
Language:English
Subjects:
COCOMO Model
Effort Estimation
Genetic Algorithm
Nature-inspired Algorithm
Optimization
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Summary:The estimation of software effort is an essential and crucial activity for the software development life cycle. In recent years, many researchers and software industries have given significant attention on the estimation of software effort. In industry, effort is used for planning, budgeting and development time calculation. Therefore a realistic effort estimation is required. Many researchers have proposed various models for software effort estimation, such as statistical models, algorithmic models, machine learning based models and nature inspired models in the past. In this research paper, a simplified genetic algorithm based model is proposed. A simplified genetic algorithm is used for optimizing the parameters of the basic COCOMO model. The proposed approach is applied on NASA software project dataset. Experimental results show better realistic estimation over the basic COCOMO.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2016.06.107