TY - GEN
T1 - Implementation of Bat Algorithm for COCOMO II Optimization
AU - Amelia Effendi, Yutika
AU - Sarno, Riyanarto
AU - Prasetyo, Joco
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/11/27
Y1 - 2018/11/27
N2 - Software effort estimation is one of the main activities in software development project, because it can indicate whether the project will be successful or failed depending on the accuracy of the estimation. There are some models to estimate effort for software development. One of the well-known models is COCOMO II. The accuracy of COCOMO II effort estimation can still be improved by optimizing its constants. Several research have been conducted to improve COCOMO II constants, such as Differential Evolution, Harmony Search and Genetic Algorithm. In this paper, a model to optimize COCOMO II constants is proposed. The optimized constants are constant A and constant B by using Bat Algorithm with Turkish project dataset. The results of experiment are compared with local calibration and COCOMO II original constants by evaluating the proposed method using Mean Magnitude Relative Error (MMRE). The results show that the proposed model has the smallest value, which means its effort estimation has closer value of actual effort than that of the other methods which exist in the Turkish project dataset.
AB - Software effort estimation is one of the main activities in software development project, because it can indicate whether the project will be successful or failed depending on the accuracy of the estimation. There are some models to estimate effort for software development. One of the well-known models is COCOMO II. The accuracy of COCOMO II effort estimation can still be improved by optimizing its constants. Several research have been conducted to improve COCOMO II constants, such as Differential Evolution, Harmony Search and Genetic Algorithm. In this paper, a model to optimize COCOMO II constants is proposed. The optimized constants are constant A and constant B by using Bat Algorithm with Turkish project dataset. The results of experiment are compared with local calibration and COCOMO II original constants by evaluating the proposed method using Mean Magnitude Relative Error (MMRE). The results show that the proposed model has the smallest value, which means its effort estimation has closer value of actual effort than that of the other methods which exist in the Turkish project dataset.
KW - COCOMO II
KW - MMRE
KW - Turkish project dataset
KW - bat algorithm
KW - software effort estimation
KW - software project
UR - https://www.scopus.com/pages/publications/85060008195
U2 - 10.1109/ISEMANTIC.2018.8549699
DO - 10.1109/ISEMANTIC.2018.8549699
M3 - Conference contribution
AN - SCOPUS:85060008195
T3 - Proceedings - 2018 International Seminar on Application for Technology of Information and Communication: Creative Technology for Human Life, iSemantic 2018
SP - 441
EP - 446
BT - Proceedings - 2018 International Seminar on Application for Technology of Information and Communication
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 3rd International Seminar on Application for Technology of Information and Communication, iSemantic 2018
Y2 - 21 September 2018 through 22 September 2018
ER -