TY - GEN
T1 - Optimization of COCOMO II coefficients using Cuckoo optimization algorithm to improve the accuracy of effort estimation
AU - Parwita, I. Made Mika
AU - Sarno, Riyanarto
AU - Puspaningrum, Alifia
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/1/19
Y1 - 2018/1/19
N2 - Software effort estimation becomes an important factor to support the success of software projects development. Uncertainty and complexity of the software can impact to inaccurate estimation directly; it becomes important challenges to improve the accuracy of estimation. Constructive Cost Model (COCOMO) II used two coefficients to estimate the effort of the software. However, using these coefficients for modern projects often leads to inaccurate estimation. To overcome these problems, Cuckoo Optimization Algorithm is proposed to improve the accuracy of the effort estimation by optimizing the coefficients. Cuckoo Optimization Algorithm (COA) is a new metaheuristic method which has been proven for a great optimization. By utilizing the coefficients of effort estimation using COA, the solution then will be evaluated by using Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE). As the result, the research showed the superiority of our proposed method compared to several methods on Turkish Software Dataset.
AB - Software effort estimation becomes an important factor to support the success of software projects development. Uncertainty and complexity of the software can impact to inaccurate estimation directly; it becomes important challenges to improve the accuracy of estimation. Constructive Cost Model (COCOMO) II used two coefficients to estimate the effort of the software. However, using these coefficients for modern projects often leads to inaccurate estimation. To overcome these problems, Cuckoo Optimization Algorithm is proposed to improve the accuracy of the effort estimation by optimizing the coefficients. Cuckoo Optimization Algorithm (COA) is a new metaheuristic method which has been proven for a great optimization. By utilizing the coefficients of effort estimation using COA, the solution then will be evaluated by using Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE). As the result, the research showed the superiority of our proposed method compared to several methods on Turkish Software Dataset.
KW - COCOMO II Model
KW - Coefficients Optimization
KW - Cuckoo Optimization Algorithm
KW - Metaheuristic Method
KW - Software Effort Estimation
UR - http://www.scopus.com/inward/record.url?scp=85041526462&partnerID=8YFLogxK
U2 - 10.1109/ICTS.2017.8265653
DO - 10.1109/ICTS.2017.8265653
M3 - Conference contribution
AN - SCOPUS:85041526462
T3 - Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017
SP - 99
EP - 104
BT - Proceedings of the 11th International Conference on Information and Communication Technology and System, ICTS 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 11th International Conference on Information and Communication Technology and System, ICTS 2017
Y2 - 31 October 2017 through 31 October 2017
ER -