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- Title
Optimizing Effort Parameter of COCOMO II Using Particle Swarm Optimization Method.
- Authors
Langsari, Kholed; Sarno, Riyanarto; Sholiq
- Abstract
Estimating the effort and cost of software is an important activity for software project managers. A poor estimate (overestimates or underestimates) will result in poor software project management. To handle this problem, many researchers have proposed various models for estimating software cost. Constructive Cost Model II (COCOMO II) is one of the best known and widely used models for estimating software costs. To estimate the cost of a software project, the COCOMO II model uses software size, cost drivers, scale factors as inputs. However, this model is still lacking in terms of accuracy. To improve the accuracy of COCOMO II model, this study examines the effect of the cost factor and scale factor in improving the accuracy of effort estimation. In this study, we initialized using Particle Swarm Optimization (PSO) to optimize the parameters in a model of COCOMO II. The method proposed is implemented using the Turkish Software Industry dataset which has 12 data items. The method can handle improper and uncertain inputs efficiently, as well as improves the reliability of software effort. The experiment results by MMRE were 34.1939%, indicating better high accuracy and significantly minimizing error 698.9461% and 104.876%.
- Subjects
COST estimates; PARTICLE swarm optimization; COMPUTER software development; FUZZY logic; SOFTWARE maintenance
- Publication
Telkomnika, 2018, Vol 16, Issue 5, p2208
- ISSN
1693-6930
- Publication type
Academic Journal
- DOI
10.12928/TELKOMNIKA.v16i5.9703